Quantifying State Transfer Strength on Graphs with Involution

This paper discusses continuous-time quantum walks and asymptotic state transfer in graphs with an involution. By providing quantitative bounds on the eigenvectors of the Hamiltonian, it provides an approach to achieving high-fidelity state transfer by strategically selecting energy potentials based on the maximum degrees of the graphs. The study also involves an analysis of the time necessary for quantum transfer to occur

A fractal effective permeability model for dual-wet porous Media

Recent studies have shown that the pores of some unconventional rocks can be categorized into hydrophilic pores that boarded by inorganic minerals such as quartz and hydrophobic pores that within the organic matter. The rock which consists of both hydrophilic and hydrophobic pores shows a dual-wettability behavior. The previously-proposed imbibition transient analysis technique has been applied in characterizing the pore size distribution of the dual-wet rocks by analyzing comparative oil and water imbibition data. On the basis of the determined pore size distribution, a fractal model for estimating effective permeability of the dual-wet rock was proposed. The proposed model, together with the imbibition transient analysis technique, is able to estimate effective permeability of the dual-wet rocks by using imbibition data. The proposed model can also estimate the effective permeability of hydrophilic pores and hydrophobic pores. The proposed model takes injection pressure, wettability behavior and pore size distribution of the dual-wet rock into the consideration. Our sensitivity analyses show that injection pressure affects effective permeability and hydrophobic permeability by controlling the water saturation within hydrophobic pores. The rock with higher volumetric fraction of hydrophilic pores tends to have higher hydrophilic permeability and lower hydrophobic permeability. By keeping the porosity constant, effective permeability decreases as the volumetric fraction of small pores increases.Cited as: Shi, Y., Guo, Y., Dehghanpour, H., Song, H. A fractal effective permeability model for dual-wet porous media. Advances in Geo-Energy Research, 2023, 8(2): 100-111. https://doi.org/10.46690/ager.2023.05.0

Yelp Reviews and Food Types: A Comparative Analysis of Ratings, Sentiments, and Topics

This study examines the relationship between Yelp reviews and food types, investigating how ratings, sentiments, and topics vary across different types of food. Specifically, we analyze how ratings and sentiments of reviews vary across food types, cluster food types based on ratings and sentiments, infer review topics using machine learning models, and compare topic distributions among different food types. Our analyses reveal that some food types have similar ratings, sentiments, and topics distributions, while others have distinct patterns. We identify four clusters of food types based on ratings and sentiments and find that reviewers tend to focus on different topics when reviewing certain food types. These findings have important implications for understanding user behavior and cultural influence on digital media platforms and promoting cross-cultural understanding and appreciation

Bioinformatic analysis identifies the immunological profile of turner syndrome with different X chromosome origins

IntroductionTurner syndrome (TS) is a chromosomal disorder that affects phenotypic females who have one intact X chromosome and complete or partial absence of the second sex chromosome in association with one or more clinical manifestations. However, the immunological profile of TS with different X chromosome origins is incompletely understood.MethodsIn this study, transcriptomic expression profiles of 26 TS (45,X) samples and 10 normal karyotype (46,XX) samples derived from GSE46687 cohort were employed. Differentially expressed immune-related genes (DEIRGs) between monosomy X TS patients with different X chromosome origins and normal females were investigated respectively. Subsequently, functional annotation, protein-protein interaction (PPI) network analysis, immunocyte infiltration evaluation, tissue-specific gene expression and Weighted gene co expression network analysis (WGCNA) were performed to explore the immunological characteristic in TS with different X chromosome origins.Results34 and 52 DEIRGs were respectively identified in 45,Xm and 45,Xp patients compared with normal individuals. The identified DEIRGs in Xm group were significantly enriched in pathways associated with cancer. In Xp TS patients, the most enriched signals were immune response-related. A majority of genes involved in the above pathways were downregulated. PPI analysis identified 4 (FLT3, IL3RA, CSF2RA, PIK3R3) and 6 (PDGFRB, CSF2, IL5, PRL, CCL17 and IL2)hub genes for Xm and Xp groups, respectively. CIBERSORT results showed that the proportion of Tregs in the Xm group and the naive B cells and resting NK cells in the Xp group significantly increased, respectively. Tissue-specific expression results indicated that BDCA4+_dentritic cells and CD19+ B cells were the prominent specific expressed tissues in Xp patients. Results of WGCNA support the above analysis.ConclusionsThis study aims at studying the immunological characteristics of TS with different X chromosome origins. Pathways in cancer in Xm group and immune response in Xp group were suppressed. 4 and 6 hub IRGs were identified as biomarkers for Xm and Xp patients, respectively. B cells played important roles in Xp patients. Further studies are needed to draw more attention to the functional validation of these hub genes and the roles of B cells

Oral microbiota of periodontal health and disease and their changes after nonsurgical periodontal therapy

This study examined the microbial diversity and community assembly of oral microbiota in periodontal health and disease and after nonsurgical periodontal treatment. The V4 region of 16S rRNA gene from DNA of 238 saliva and subgingival samples of 21 healthy and 48 diseased subjects was amplified and sequenced. Among 1979 OTUs identified, 28 were overabundant in diseased plaque. Six of these taxa were also overabundant in diseased saliva. Twelve OTUs were overabundant in healthy plaque. There was a trend for disease-associated taxa to decrease and health-associated taxa to increase after treatment with notable variations among individual sites. Network analysis revealed modularity of the microbial communities and identified several health- and disease-specific modules. Ecological drift was a major factor that governed community turnovers in both plaque and saliva. Dispersal limitation and homogeneous selection affected the community assembly in plaque, with the additional contribution of homogenizing dispersal for plaque within individuals. Homogeneous selection and dispersal limitation played important roles, respectively, in healthy saliva and diseased pre-treatment saliva between individuals. Our results revealed distinctions in both taxa and assembly processes of oral microbiota between periodontal health and disease. Furthermore, the community assembly analysis has identified potentially effective approaches for managing periodontitis

MindShift: Leveraging Large Language Models for Mental-States-Based Problematic Smartphone Use Intervention

Problematic smartphone use negatively affects physical and mental health. Despite the wide range of prior research, existing persuasive techniques are not flexible enough to provide dynamic persuasion content based on users' physical contexts and mental states. We first conduct a Wizard-of-Oz study (N=12) and an interview study (N=10) to summarize the mental states behind problematic smartphone use: boredom, stress, and inertia. This informs our design of four persuasion strategies: understanding, comforting, evoking, and scaffolding habits. We leverage large language models (LLMs) to enable the automatic and dynamic generation of effective persuasion content. We develop MindShift, a novel LLM-powered problematic smartphone use intervention technique. MindShift takes users' in-the-moment physical contexts, mental states, app usage behaviors, users' goals & habits as input, and generates high-quality and flexible persuasive content with appropriate persuasion strategies. We conduct a 5-week field experiment (N=25) to compare MindShift with baseline techniques. The results show that MindShift significantly improves intervention acceptance rates by 17.8-22.5% and reduces smartphone use frequency by 12.1-14.4%. Moreover, users have a significant drop in smartphone addiction scale scores and a rise in self-efficacy. Our study sheds light on the potential of leveraging LLMs for context-aware persuasion in other behavior change domains