Fundamental aspects of solid dispersion technology for poorly soluble drugs

AbstractThe solid dispersion has become an established solubilization technology for poorly water soluble drugs. Since a solid dispersion is basically a drug–polymer two-component system, the drug–polymer interaction is the determining factor in its design and performance. In this review, we summarize our current understanding of solid dispersions both in the solid state and in dissolution, emphasizing the fundamental aspects of this important technology

Prediction of Water Consumption in Hospitals Based on a Modified Grey GM (0, 1∣sin) Model of Oscillation Sequence: The Example of Wuhan City

Water shortage is one of the main factors limiting urban construction and development. Scientific forecasting of water consumption is an important approach for the rational allocation of water resources. Taking the hospitals in Wuhan City as an example and basing the analysis on the characteristics of actual water consumption, we proposed a modified grey GM (0, 1∣sin) model of oscillation sequence. Using the grey theory, the variable weight-strengthening buffer operator (VWSBO) was introduced into this model to weaken the interference of the disturbance term on the data sequence. The actual quarterly total water consumption data for hospitals in Wuhan City during the period from 2010 to 2012 were used to verify the effectiveness and practicality of this modified grey GM (0, 1∣sin) model in predicting water consumption. In terms of the model’s fitting performance, the mean absolute percentage error (MAPE) of the modified model was 3.77%, indicating a higher prediction accuracy than the traditional grey GM (0, 1∣sin) model of oscillation sequences. Therefore, the modified grey GM (0, 1∣sin) model we established in this study can provide a scientific reference for administrative departments to forecast water consumption

Intergenerational transmission of education in China: New evidence from the Chinese Cultural Revolution

This paper estimates the effect of parental education on children’s education by using instruments generated by the Chinese Cultural Revolution, and further explores the mechanisms of this causal relationship. Several important findings stand out from our empirical analyses. We find a larger intergenerational persistence in education for higher level in urban areas but for a lower level of education in rural areas. The main results from instrumental variable estimation show that the nurture effect is larger and more significant for fathers than for mothers. A deeper investigation of the mechanism behind this nurture effect informs us that a father’s education passes on to his children’s education partly through the income channel. Another notable finding is that even after controlling for fathers’ income, parental education still has a significantly positive effect on children’s education through the nurture effect. This indicates that beyond the income channel, there may exist other channels such as better home environment, which deserve to be explored in future research.Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/147763/1/rode12558_am.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/147763/2/rode12558.pd

KICGPT: Large Language Model with Knowledge in Context for Knowledge Graph Completion

Knowledge Graph Completion (KGC) is crucial for addressing knowledge graph incompleteness and supporting downstream applications. Many models have been proposed for KGC. They can be categorized into two main classes: triple-based and text-based approaches. Triple-based methods struggle with long-tail entities due to limited structural information and imbalanced entity distributions. Text-based methods alleviate this issue but require costly training for language models and specific finetuning for knowledge graphs, which limits their efficiency. To alleviate these limitations, in this paper, we propose KICGPT, a framework that integrates a large language model (LLM) and a triple-based KGC retriever. It alleviates the long-tail problem without incurring additional training overhead. KICGPT uses an in-context learning strategy called Knowledge Prompt, which encodes structural knowledge into demonstrations to guide the LLM. Empirical results on benchmark datasets demonstrate the effectiveness of KICGPT with smaller training overhead and no finetuning.Comment: Accepted to EMNLP 2023 Finding

Application of Wireless Communication and GIS in Agricultural Environment Monitoring

The SMS/GPRS technology and seamless integration of GIS technology were used to implement remote data real-time transmission and management analysis in agricultural environment monitoring. Through SMS/GPRS technology this system realized wireless real-time transmission of remote monitoring data. Based on the GIS visualization technology and spatial analysis the monitoring data were displayed visually as well as location of pollution area was realized. System mainly consists of three modules: monitor communication center, information center and GIS environment monitoring information management. The overall design system in fully reflects the GIS, wireless transmission, environment monitoring seamless integration of the three modules. Development language is Visual Studio2005 VC.NET comprehensive use of MFC and CRL and Oracle9i database is adapted to integratedly access attribute data and the of spatial data, using MapX component to implement map visualization display and spatial geographical analysis. The system is suitable for departments of agriculture to acquire and communicate the environmental monitoring data, to manage the GIS, and to analyze the decision