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

Research on Online Reviews Reliability

This study examines the factors that have an impact on online reviews reliability. A theoretical framework was built and empirically tested with a sample of 200 interviewees. Results of structural equation model show that the online reviews quality and perceived risk have positive impact on online review reliability. Accordingly, online review value and number have positive impact on online review quality, customer involvement and reviewer acception have positive impact on perceived risk. The results of this study also suggest that the character of online review and reviewer indirectly impact review reliability by impacting intermediate variables

QS-TTS: Towards Semi-Supervised Text-to-Speech Synthesis via Vector-Quantized Self-Supervised Speech Representation Learning

This paper proposes a novel semi-supervised TTS framework, QS-TTS, to improve TTS quality with lower supervised data requirements via Vector-Quantized Self-Supervised Speech Representation Learning (VQ-S3RL) utilizing more unlabeled speech audio. This framework comprises two VQ-S3R learners: first, the principal learner aims to provide a generative Multi-Stage Multi-Codebook (MSMC) VQ-S3R via the MSMC-VQ-GAN combined with the contrastive S3RL, while decoding it back to the high-quality audio; then, the associate learner further abstracts the MSMC representation into a highly-compact VQ representation through a VQ-VAE. These two generative VQ-S3R learners provide profitable speech representations and pre-trained models for TTS, significantly improving synthesis quality with the lower requirement for supervised data. QS-TTS is evaluated comprehensively under various scenarios via subjective and objective tests in experiments. The results powerfully demonstrate the superior performance of QS-TTS, winning the highest MOS over supervised or semi-supervised baseline TTS approaches, especially in low-resource scenarios. Moreover, comparing various speech representations and transfer learning methods in TTS further validates the notable improvement of the proposed VQ-S3RL to TTS, showing the best audio quality and intelligibility metrics. The trend of slower decay in the synthesis quality of QS-TTS with decreasing supervised data further highlights its lower requirements for supervised data, indicating its great potential in low-resource scenarios

Study Design and Data Analysis of Artificial Pancreas Device Systems with Closed-Loop Glucose-Sensing Insulin Delivery

Objective: The objective of this article is to provide a high-profile review and discussion on the study design and statistical analysis of pivotal clinical trials conducted to demonstrate the safety and effectiveness of closed-loop investigational artificial pancreas device systems (APDSs) in premarket approval applications. Methods: The United States Food and Drug Administration (FDA) guidance on the content of investigational device exemption and premarket approval applications for APDSs is reviewed with special emphasis on study design and statistical analysis of the pivotal clinical trials. The two pivotal studies for the MiniMed 670G hybrid closed-loop system by Medtronic in their premarket approval application are summarized and discussed. Results: The United States FDA established detailed recommendations on the study design and statistical analysis of pivotal clinical trials for the industry that seek market investigational APDSs and for FDA scientific reviewers that regulate the device applications. The recommendations cover specifics regarding patient population, clinical endpoints, and strategies for data analysis. However, the two pivotal studies that demonstrated the effectiveness of the FDA-approved MiniMed 670G hybrid closed-loop system were not typical randomized controlled trials as per FDA recommendations. Conclusion: The development and regulation of investigational APDSs require careful and sophisticated clinical study designs and data analysis in premarket approval applications. The regulatory evaluation process of the APDSs is rather complicated since the devices consist of multiple components that collaboratively function to mimic human pancreases

ToxicChat: Unveiling Hidden Challenges of Toxicity Detection in Real-World User-AI Conversation

Despite remarkable advances that large language models have achieved in chatbots, maintaining a non-toxic user-AI interactive environment has become increasingly critical nowadays. However, previous efforts in toxicity detection have been mostly based on benchmarks derived from social media content, leaving the unique challenges inherent to real-world user-AI interactions insufficiently explored. In this work, we introduce ToxicChat, a novel benchmark based on real user queries from an open-source chatbot. This benchmark contains the rich, nuanced phenomena that can be tricky for current toxicity detection models to identify, revealing a significant domain difference compared to social media content. Our systematic evaluation of models trained on existing toxicity datasets has shown their shortcomings when applied to this unique domain of ToxicChat. Our work illuminates the potentially overlooked challenges of toxicity detection in real-world user-AI conversations. In the future, ToxicChat can be a valuable resource to drive further advancements toward building a safe and healthy environment for user-AI interactions

Miniaturized Computational Photonic Molecule Spectrometer

Miniaturized spectrometry system is playing an essential role for materials analysis in the development of in-situ or portable sensing platforms across research and industry. However, there unavoidably exists trade-offs between the resolution and operation bandwidth as the device scale down. Here, we report an extreme miniaturized computational photonic molecule (PM) spectrometer utilizing the diverse spectral characteristics and mode-hybridization effect of split eigenfrequencies and super-modes, which effectively eliminates the inherent periodicity and expands operation bandwidth with ultra-high spectral resolution. These results of dynamic control of the frequency, amplitude, and phase of photons in the photonic multi-atomic systems, pave the way to the development of benchtop sensing platforms for applications previously unfeasible due to resolution-bandwidth-footprint limitations, such as in gas sensing or nanoscale biomedical sensing

Effect of over-ply on moisture absorption behavior of scarf-repaired composite laminate

The over-ply covering the bondline in scarf-repaired laminates can avoid direct exposure of the adhesive to moisture environment which would decrease the properties of the adhesive. The effect of the over-ply on moisture absorption behavior of scarf-repaired composite laminate was studied in this paper. 3D finite element models (FEMs) of scarf-repaired laminates with and without over-ply were established to simulate the moisture absorption behavior and verified by experimental results. Then these models were used to investigate the effects of some factors, including over-ply type, configuration, direction and number, on moisture absorption behavior of the repaired structures, especially of the adhesive. The results show that the over-ply can efficiently decelerate moisture absorption of the adhesive and delay the time of its moisture absorption equilibrium. Over-ply type has effect on moisture absorption of the adhesive. Woven over-ply is more effective to protect the adhesive in repaired laminates from moisture absorption than unidirectional over-ply. For the laminates with only large-circle bonding surface covered, over-ply lap length, configuration and direction are not very important parameters to affect the moisture absorption

Whole-exome sequencing identifies susceptibility genes and pathways for idiopathic pulmonary fibrosis in the Chinese population

Genetic factors play a role in the risk of idiopathic pulmonary fibrosis (IPF). Specifically, MUC5B rs35705950 non-risk alleles and immunologic aberrations were associated with the IPF’s progression. However, rare genetic variants have not been systematically investigated in Chinese IPF patients. In this study, we aimed to improve understanding of the genetic architecture of IPF in the Chinese population and to assess whether rare protein-coding variants in the immunity pathway genes are enriched in the IPF patients with non-risk alleles at rs35705950. A case–control exome-wide study including 110 IPF patients and 60 matched healthy controls was conducted. rs35705950 was genotyped by Sanger sequencing. To identify genes enriched in IPF, gene-based association analyses were performed. Identified genes were included for further pathway analyses using gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG). Associations between rs35705950 and genes enriched in the immunity pathway were also tested. 226 genes that were enriched with deleterious variants were identified in IPF patients. Out of them, 36 genes were significantly enriched in GO and KEGG pathways in the IPF. Pathway analyses implicated that these genes were involved in the immune response and cell adhesion. Rare protein-altering variants in genes related to the immunity pathway did not significantly differ between patients with a MUC5B risk allele and individuals without risk allele. We drafted a comprehensive mutational landscape of rare protein-coding variants in the Chinese IPF and identified genes related to immune response and cell adhesion. These results partially explain changes in gene expression involved in the immunity/inflammatory pathways in IPF patients