Density functional plus dynamical mean field theory of the metal-insulator transition in early transition metal oxides

The combination of density functional theory and single-site dynamical mean-field theory, using both Hartree and full continuous-time quantum Monte Carlo impurity solvers, is used to study the metal-insulator phase diagram of perovskite transition-metal oxides of the form $AB$O$_3$ with a rare-earth ion $A$=Sr, La, Y and transition metal $B$=Ti, V, Cr. The correlated subspace is constructed from atomiclike $d$ orbitals defined using maximally localized Wannier functions derived from the full $p$-$d$ manifold; for comparison, results obtained using a projector method are also given. Paramagnetic DFT+DMFT computations using full charge self-consistency along with the standard "fully localized limit" (FLL) double counting are shown to incorrectly predict that LaTiO$_3$, YTiO$_3$, LaVO$_3$ and SrMnO$_3$ are metals. A more general examination of the dependence of physical properties on the mean $p$-$d$ energy splitting, the occupancy of the correlated $d$ states, the double-counting correction, and the lattice structure demonstrates the importance of charge-transfer physics even in the early transition-metal oxides and elucidates the factors underlying the failure of the standard approximations. If the double counting is chosen to produce a $p$-$d$ splitting consistent with experimental spectra, single-site dynamical mean-field theory provides a reasonable account of the materials properties. The relation of the results to those obtained from "$d$-only" models in which the correlation problem is based on the frontier orbital $p$-$d$ antibonding bands is determined. It is found that if an effective interaction $U$ is properly chosen the $d$-only model provides a good account of the physics of the $d^1$ and $d^2$ materials.Comment: 19 pages, 16 figure

Word Semantic Similarity Calculation Based on Domain Knowledge and HowNet

Word semantic similarity is the foundation of semantic processing, and is a key issue in many applications. This paper argues that word semantic similarity should associate with domain knowledge, which traditional methods did not take into account. In order to adopt domain knowledge into semantic similarity measurement, this paper proposed a sensitive words sets approach. For this purpose, we also propose a new approach for sememe similarity calculation. This method distinguishes three different positional relationships between two sememes, and the results have shown that our method overperformed than other methods based on a Chinese knowledge base ‘HowNet’. DOI : http://dx.doi.org/10.11591/telkomnika.v12i2.441

The Effect of Air leakage through the Air Cavities of Building Walls on Mold Growth Risks

Mold growth poses a high risk to a large number of existing buildings and their users. Air leakage through the air cavities of the building walls, herein gaps between walls and air conditioner pipes penetrating the walls, may increase the risks of interstitial condensation, mold growth and other moisture-related problems. In order to quantify the mold growth risks due to air leakage through air cavity, an office room in a historical masonry building in Nanjing, China, was selected, and its indoor environment has been studied. Fungi colonization can be seen on the surface of air conditioner pipes in the interior side near air cavity of the wall. Hygrothermometers and thermocouples logged interior and exterior temperature and relative humidity from June 2018 to January 2020. The measured data show that in summer the outdoor humidity remained much higher than that of the room, while the temperature near the air cavity stays lower than those of the other parts in the room. Hot and humid outdoor air may condense on the cold wall surface near an air cavity. A two-dimensional hygrothermal simulation was made. Air leakage through the air cavities of walls proved to be a crucial factor for mold growth

Interferon regulatory factor 5: a potential target for therapeutic intervention in inflammatory diseases

Interferon regulatory factor 5 (IRF5) is a critical transcription factor in the IRF family, playing a pivotal role in modulating immune responses, particularly within the innate immune system. IRF5 regulates the expression of type I interferons (IFNs), proinflammatory cytokines, and other immune-related genes, essential for effective host defense against infections and immune surveillance. Its functions, however, are diverse and highly context-dependent, adapting to different immune challenges and tissue environments. Studies have demonstrated that dysregulated IRF5 activation contributes to the pathogenesis of numerous diseases, including cancer, autoimmune disorders, and chronic inflammatory conditions such as systemic lupus erythematosus (SLE) and rheumatoid arthritis (RA). This dysregulation underscores the dual role of IRF5, both in immune protection and in driving pathological inflammation. Given its significant involvement in both physiological and pathological processes, IRF5 presents a promising therapeutic target for managing diseases characterized by excessive inflammation and immune dysregulation. However, developing effective molecules to specifically modulate the IRF5 pathway remains challenging, with limited therapeutic agents available for clinical application. In this review, we examine the diverse roles of IRF5 in various disease contexts, the mechanisms by which IRF5 contributes to disease progression, and the potential therapeutic strategies targeting IRF5. Additionally, we discuss potential complications and risks associated with IRF5-targeted therapies, including the balance between dampening pathological inflammation and preserving essential immune functions. This exploration highlights both the therapeutic potential and the complexity of modulating IRF5 activity in clinical settings

Dynamic Prognosis Prediction for Patients on DAPT After Drug-Eluting Stent Implantation: Model Development and Validation

BACKGROUND: The rapid evolution of artificial intelligence (AI) in conjunction with recent updates in dual antiplatelet therapy (DAPT) management guidelines emphasizes the necessity for innovative models to predict ischemic or bleeding events after drug-eluting stent implantation. Leveraging AI for dynamic prediction has the potential to revolutionize risk stratification and provide personalized decision support for DAPT management. METHODS AND RESULTS: We developed and validated a new AI-based pipeline using retrospective data of drug-eluting stent-treated patients, sourced from the Cerner Health Facts data set (n=98 236) and Optum\u27s de-identified Clinformatics Data Mart Database (n=9978). The 36 months following drug-eluting stent implantation were designated as our primary forecasting interval, further segmented into 6 sequential prediction windows. We evaluated 5 distinct AI algorithms for their precision in predicting ischemic and bleeding risks. Model discriminative accuracy was assessed using the area under the receiver operating characteristic curve, among other metrics. The weighted light gradient boosting machine stood out as the preeminent model, thus earning its place as our AI-DAPT model. The AI-DAPT demonstrated peak accuracy in the 30 to 36 months window, charting an area under the receiver operating characteristic curve of 90% [95% CI, 88%-92%] for ischemia and 84% [95% CI, 82%-87%] for bleeding predictions. CONCLUSIONS: Our AI-DAPT excels in formulating iterative, refined dynamic predictions by assimilating ongoing updates from patients\u27 clinical profiles, holding value as a novel smart clinical tool to facilitate optimal DAPT duration management with high accuracy and adaptability

Sleep neuroimaging: Review and future directions

SummarySleep research has evolved considerably since the first sleep electroencephalography recordings in the 1930s and the discovery of well‐distinguishable sleep stages in the 1950s. While electrophysiological recordings have been used to describe the sleeping brain in much detail, since the 1990s neuroimaging techniques have been applied to uncover the brain organization and functional connectivity of human sleep with greater spatial resolution. The combination of electroencephalography with different neuroimaging modalities such as positron emission tomography, structural magnetic resonance imaging and functional magnetic resonance imaging imposes several challenges for sleep studies, for instance, the need to combine polysomnographic recordings to assess sleep stages accurately, difficulties maintaining and consolidating sleep in an unfamiliar and restricted environment, scanner‐induced distortions with physiological artefacts that may contaminate polysomnography recordings, and the necessity to account for all physiological changes throughout the sleep cycles to ensure better data interpretability. Here, we review the field of sleep neuroimaging in healthy non‐sleep‐deprived populations, from early findings to more recent developments. Additionally, we discuss the challenges of applying concurrent electroencephalography and imaging techniques to sleep, which consequently have impacted the sample size and generalizability of studies, and possible future directions for the field

Aggregation-Induced Emission (AIE), Life and Health

Light has profoundly impacted modern medicine and healthcare, with numerous luminescent agents and imaging techniques currently being used to assess health and treat diseases. As an emerging concept in luminescence, aggregation-induced emission (AIE) has shown great potential in biological applications due to its advantages in terms of brightness, biocompatibility, photostability, and positive correlation with concentration. This review provides a comprehensive summary of AIE luminogens applied in imaging of biological structure and dynamic physiological processes, disease diagnosis and treatment, and detection and monitoring of specific analytes, followed by representative works. Discussions on critical issues and perspectives on future directions are also included. This review aims to stimulate the interest of researchers from different fields, including chemistry, biology, materials science, medicine, etc., thus promoting the development of AIE in the fields of life and health

Therapeutic Potential of Targeting the PERK Signaling Pathway in Ischemic Stroke

Many pathologic states can lead to the accumulation of unfolded/misfolded proteins in cells. This causes endoplasmic reticulum (ER) stress and triggers the unfolded protein response (UPR), which encompasses three main adaptive branches. One of these UPR branches is mediated by protein kinase RNA-like ER kinase (PERK), an ER stress sensor. The primary consequence of PERK activation is the suppression of global protein synthesis, which reduces ER workload and facilitates the recovery of ER function. Ischemic stroke induces ER stress and activates the UPR. Studies have demonstrated the involvement of the PERK pathway in stroke pathophysiology; however, its role in stroke outcomes requires further clarification. Importantly, considering mounting evidence that supports the therapeutic potential of the PERK pathway in aging-related cognitive decline and neurodegenerative diseases, this pathway may represent a promising therapeutic target in stroke. Therefore, in this review, our aim is to discuss the current understanding of PERK in ischemic stroke, and to summarize pharmacologic tools for translational stroke research that targets PERK and its associated pathways

Career Education Skills and Career Adaptability among College Students in China: The Mediating Role of Career Decision-Making Self-Efficacy

In the past, the shift in career patterns and the unprecedented disruptions caused by events such as COVID-19 have posed notable challenges for job seekers. This holds particularly true for college students who are preparing to enter the workforce. In this context, enhancing career adaptability plays a vital role in shaping their career development. The primary objective of this research was to investigate the relationship between career education skills and career adaptability among 273 undergraduate students in China. Additionally, the study aimed to explore the mediating effect of career decision-making self-efficacy in shaping this relationship. The findings of the correlation analysis indicate a significant positive correlation between career education skills and career adaptability. Moreover, the results of the mediation model revealed that career education skills significantly contribute to improving career adaptability along with the mediating effect of college students’ self-efficacy in making career decisions. This study suggests that universities should prioritize the development and expansion of career education initiatives. They should not only help establish clear career goals for college students but also cultivate a positive and flexible career outlook to assist them in better adapting to various changes that may arise throughout their career journeys

Evaluation of mould growth risks due to air leakage through air cavity of the building walls

Mould growth causes damage and poses high risk to a large number of existing buildings and their users. Air leakage through air cavity of the building walls, such as gaps between walls and some pipes penetrating the walls, produces obvious hygrothermal exchange, altering the temperature and humidity distribution of the walls. It would promote condensation and mould growth. Air cavity are common on the walls of existing buildings. In order to make a quantitative analysis on the mould growth risks due to air leakage through air cavity, an office room in an existing building in Nanjing, China was selected and hygrothermometers were arranged indoor and outdoor for monitoring. The measured results showed the room was in high temperature and relative humidity from June to early September. Two-dimensional hygrothermal simulation was made to investigate the hygrothermal conditions of the walls with air cavity, using the measured data as boundary conditions and validation for the numerical simulation. Mould growth risks under these situations were estimated