Evaluation of different setups for the measurement of drug penetration into the nail

The aim of this study was to conduct permeation using 3 different setups: Franz diffusion cells, wet cotton ball, and agar gel to investigate whether the same permeation results would be obtained with a nail lacquer formulation. Subsequently, 4 nail lacquers were used in 2 of permeation setups to detect whether the order of best to worst formulation was the same in the different setups

A Quantitative Review on Language Model Efficiency Research

Language models (LMs) are being scaled and becoming powerful. Improving their efficiency is one of the core research topics in neural information processing systems. Tay et al. (2022) provided a comprehensive overview of efficient Transformers that have become an indispensable staple in the field of NLP. However, in the section of "On Evaluation", they left an open question "which fundamental efficient Transformer one should consider," answered by "still a mystery" because "many research papers select their own benchmarks." Unfortunately, there was not quantitative analysis about the performances of Transformers on any benchmarks. Moreover, state space models (SSMs) have demonstrated their abilities of modeling long-range sequences with non-attention mechanisms, which were not discussed in the prior review. This article makes a meta analysis on the results from a set of papers on efficient Transformers as well as those on SSMs. It provides a quantitative review on LM efficiency research and gives suggestions for future research.Comment: 29 pages, 24 table

Embedding Mental Health Discourse for Community Recommendation

Our paper investigates the use of discourse embedding techniques to develop a community recommendation system that focuses on mental health support groups on social media. Social media platforms provide a means for users to anonymously connect with communities that cater to their specific interests. However, with the vast number of online communities available, users may face difficulties in identifying relevant groups to address their mental health concerns. To address this challenge, we explore the integration of discourse information from various subreddit communities using embedding techniques to develop an effective recommendation system. Our approach involves the use of content-based and collaborative filtering techniques to enhance the performance of the recommendation system. Our findings indicate that the proposed approach outperforms the use of each technique separately and provides interpretability in the recommendation process.Comment: Accepted to the 4th workshop on Computational Approaches to Discourse (CODI-2023) at ACL 202

Effects of elevated ambient temperature on embryo implantation in rats

Implantation is a crucial step in mammalian reproduction as it is a gateway to further embryonic development and successful pregnancy. Changes in the environmental factors, such as temperature have adverse effects on reproduction. However, the impact of elevated temperature on the implantation process is not well defined. The objective of this study was to investigate the possible effect of elevated ambient temperature on implantation time and rate. The results revealed that exposure to elevated ambient temperature leads to a delayed implantation and reduced number of implantation sites in Sprague Dawley rats. Moreover, the exposure to elevated temperature resulted in change in the progesterone and estradiol patterns during the implantation time. These findings indicate that elevated temperature disturbs the implantation process.Key words: Elevated temperature, implantation time, number of implantation sites, progesterone and estradiol

Carbon Nanofibers-Based Nanoconfined Liquid Phase Filtration for the Rapid Removal of Chlorinated Pesticides from Ginseng Extracts.

A rapid nanoconfined liquid phase filtration system (NLPF) based on solvent-confined carbon nanofibers/carbon fiber materials (CNFs/CFs) was proposed to effectively remove chlorinated pesticides from ginsenosides-containing ginseng extracts. A series of major parameters that may affect the separation performance of the CNFs-NLPF method were extensively investigated, including the water solubility of nanoconfined solvents, filtration rate, ethanol content of the ginseng extracts, and reusability of the material for repeated adsorption. The developed method showed a high removal efficiency of pesticides (85.5-97.5%), high retainment rate of ginsenosides (95.4-98.9%), and consistent reproducibility (RSD < 11.8%). Furthermore, the feasibility of the CNFs-NLPF technique to be scaled-up for industrial application was systematically explored by analyzing large-volume ginseng extract (1 L), which also verified its excellent modifiable characteristic. This filtration method exhibits promising potential as a practical tool for removing pesticide residues and other organic pollutants in food samples to assure food quality and safeguard human health

Operando real-space imaging of a structural phase transformation in a high-voltage electrode

Discontinuous solid-solid phase transformations play a pivotal role in determining properties of rechargeable battery electrodes. By leveraging operando Bragg Coherent Diffractive Imaging (BCDI), we investigate the discontinuous phase transformation in LixNi0.5Mn1.5O4 within a fully operational battery. Throughout Li-intercalation, we directly observe the nucleation and growth of the Li-rich phase within the initially charged Li-poor phase in a 500 nm particle. Supported by the microelasticity model, the operando imaging unveils an evolution from a curved coherent to planar semi-coherent interface driven by dislocation dynamics. We hypothesize these dislocations exhibit a glissile motion that facilitates interface migration without diffusion of host ions, leaving the particle defect-free post-transformation. Our data indicates negligible kinetic limitations impacting the transformation kinetics, even at discharge rates as fast as C/2. This study underscores BCDI's capability to provide operando insights into nanoscale phase transformations, offering valuable guidance for electrochemical materials design and optimization

Smad3 promotes cancer progression by inhibiting E4BP4-mediated NK cell development

published_or_final_versio

Comparison of techniques for handling missing covariate data within prognostic modelling studies: a simulation study

Background: There is no consensus on the most appropriate approach to handle missing covariate data within prognostic modelling studies. Therefore a simulation study was performed to assess the effects of different missing data techniques on the performance of a prognostic model. Methods: Datasets were generated to resemble the skewed distributions seen in a motivating breast cancer example. Multivariate missing data were imposed on four covariates using four different mechanisms; missing completely at random (MCAR), missing at random (MAR), missing not at random (MNAR) and a combination of all three mechanisms. Five amounts of incomplete cases from 5% to 75% were considered. Complete case analysis (CC), single imputation (SI) and five multiple imputation (MI) techniques available within the R statistical software were investigated: a) data augmentation (DA) approach assuming a multivariate normal distribution, b) DA assuming a general location model, c) regression switching imputation, d) regression switching with predictive mean matching (MICE-PMM) and e) flexible additive imputation models. A Cox proportional hazards model was fitted and appropriate estimates for the regression coefficients and model performance measures were obtained. Results: Performing a CC analysis produced unbiased regression estimates, but inflated standard errors, which affected the significance of the covariates in the model with 25% or more missingness. Using SI, underestimated the variability; resulting in poor coverage even with 10% missingness. Of the MI approaches, applying MICE-PMM produced, in general, the least biased estimates and better coverage for the incomplete covariates and better model performance for all mechanisms. However, this MI approach still produced biased regression coefficient estimates for the incomplete skewed continuous covariates when 50% or more cases had missing data imposed with a MCAR, MAR or combined mechanism. When the missingness depended on the incomplete covariates, i.e. MNAR, estimates were biased with more than 10% incomplete cases for all MI approaches. Conclusion: The results from this simulation study suggest that performing MICE-PMM may be the preferred MI approach provided that less than 50% of the cases have missing data and the missing data are not MNAR

Nucleation of dislocations and their dynamics in layered oxide cathode materials during battery charging

Defects and their interactions in crystalline solids often underpin material properties and functionality as they are decisive for stability, result in enhanced diffusion, and act as a reservoir of vacancies. Recently, lithium-rich layered oxides have emerged among the leading candidates for the next-generation energy storage cathode material, delivering 50 % excess capacity over commercially used compounds. Oxygen-redox reactions are believed to be responsible for the excess capacity, however, voltage fading has prevented commercialization of these new materials. Despite extensive research the understanding of the mechanisms underpinning oxygen-redox reactions and voltage fade remain incomplete. Here, using operando three-dimensional Bragg coherent diffractive imaging, we directly observe nucleation of a mobile dislocation network in nanoparticles of lithium-rich layered oxide material. Surprisingly, we find that dislocations form more readily in the lithium-rich layered oxide material as compared with a conventional layered oxide material, suggesting a link between the defects and the anomalously high capacity in lithium-rich layered oxides. The formation of a network of partial dislocations dramatically alters the local lithium environment and contributes to the voltage fade. Based on our findings we design and demonstrate a method to recover the original high voltage functionality. Our findings reveal that the voltage fade in lithium-rich layered oxides is reversible and call for new paradigms for improved design of oxygen-redox active materials