Agreement in the scoring of respiratory events and sleep among international sleep centers.

To access publisher's full text version of this article. Please click on the hyperlink in Additional Links field.Abstract STUDY OBJECTIVES: The American Academy of Sleep Medicine (AASM) guidelines for polysomnography (PSG) scoring are increasingly being adopted worldwide, but the agreement among international centers in scoring respiratory events and sleep stages using these guidelines is unknown. We sought to determine the interrater agreement of PSG scoring among international sleep centers. DESIGN: Prospective study of interrater agreement of PSG scoring. SETTING: Nine center-members of the Sleep Apnea Genetics International Consortium (SAGIC). MEASUREMENTS AND RESULTS: Fifteen previously recorded deidentified PSGs, in European Data Format, were scored by an experienced technologist at each site after they were imported into the locally used analysis software. Each 30-sec epoch was manually scored for sleep stage, arousals, apneas, and hypopneas using the AASM recommended criteria. The computer-derived oxygen desaturation index (ODI) was also recorded. The primary outcome for analysis was the intraclass correlation coefficient (ICC) of the apnea-hypopnea index (AHI). The ICCs of the respiratory variables were: AHI = 0.95 (95% confidence interval: 0.91-0.98), total apneas = 0.77 (0.56-0.87), total hypopneas = 0.80 (0.66-0.91), and ODI = 0.97 (0.93-0.99). The kappa statistics for sleep stages were: wake = 0.78 (0.77-0.79), nonrapid eye movement = 0.77 (0.76-0.78), N1 = 0.31 (0.30-0.32), N2 = 0.60 (0.59-0.61), N3 = 0.67 (0.65-0.69), and rapid eye movement = 0.78 (0.77-0.79). The ICC of the arousal index was 0.68 (0.50-0.85). CONCLUSION: There is strong agreement in the scoring of respiratory events among the SAGIC centers. There is also substantial epoch-by-epoch agreement in scoring sleep variables. Our results suggest that centralized scoring of PSGs may not be necessary in future research collaboration among international sites where experienced, well-trained scorers are involved.NHLBI P01 HL094307 HL093463 Tzagournis Medical Research Endowment Funds of The Ohio State Universit

A Practical and Secure Stateless Order Preserving Encryption for Outsourced Databases

Order-preserving encryption (OPE) plays an important role in securing outsourced databases. OPE schemes can be either Stateless or Stateful. Stateful schemes can achieve the ideal security of order-preserving encryption, i.e., “reveal no information about the plaintexts besides order.” However, comparing to stateless schemes, stateful schemes require maintaining some state information locally besides encryption keys and the ciphertexts are mutable. On the other hand, stateless schemes only require remembering encryption keys and thus is more efficient. It is a common belief that stateless schemes cannot provide the same level of security as stateful ones because stateless schemes reveal the relative distance among their corresponding plaintext. In real world applications, such security defects may lead to the leakage of statistical and sensitive information, e.g., the data distribution, or even negates the whole encryption. In this paper, we propose a practical and secure stateless order-preserving encryption scheme. With prior knowledge of the data to be encrypted, our scheme can achieve IND-CCPA (INDistinguishability under Committed ordered Chosen Plaintext Attacks) security for static data set. Though the IND-CCPA security can\u27t be met for dynamic data set, our new scheme can still significantly improve the security in real world applications. Along with the encryption scheme, in this paper we also provide methods to eliminate access pattern leakage in communications and thus prevents some common attacks to OPE schemes in practice

Low-Resource Music Genre Classification with Advanced Neural Model Reprogramming

Transfer learning (TL) approaches have shown promising results when handling tasks with limited training data. However, considerable memory and computational resources are often required for fine-tuning pre-trained neural networks with target domain data. In this work, we introduce a novel method for leveraging pre-trained models for low-resource (music) classification based on the concept of Neural Model Reprogramming (NMR). NMR aims at re-purposing a pre-trained model from a source domain to a target domain by modifying the input of a frozen pre-trained model. In addition to the known, input-independent, reprogramming method, we propose an advanced reprogramming paradigm: Input-dependent NMR, to increase adaptability to complex input data such as musical audio. Experimental results suggest that a neural model pre-trained on large-scale datasets can successfully perform music genre classification by using this reprogramming method. The two proposed Input-dependent NMR TL methods outperform fine-tuning-based TL methods on a small genre classification dataset.Comment: Submitted to ICASSP 2023. Some experimental results were reduced due to the space limit. The implementation will be available at https://github.com/biboamy/music-repr

Current concepts on oxidative/carbonyl stress, inflammation and epigenetics in pathogenesis of chronic obstructive pulmonary disease

Chronic obstructive pulmonary disease (COPD) is a global health problem, and current therapy for COPD is poorly effective and the mainstays of pharmacotherapy are bronchodilators. A better understanding of the pathobiology of COPD is critical for the development of novel therapies. In the present review, we have discussed the roles of oxidative/aldehyde stress, inflammation/immunity, and chromatin remodeling in the pathogenesis of COPD. Imbalance of oxidant/antioxidant balance caused by cigarette smoke and other pollutants/biomass fuels plays an important role in the pathogenesis of COPD by regulating redox-sensitive transcription factors (e.g. NF-κB), autophagy and unfolded protein response leading to chronic lung inflammatory response. Cigarette smoke also activates canonical/alternative NF-κB pathways and their upstream kinases leading to sustained inflammatory response in lungs. Recently, epigenetic regulation has been shown to be critical for the development of COPD because the expression/activity of enzymes that regulate these epigenetic modifications have been reported to be abnormal in airways of COPD patients. Hence, the significant advances made in understanding the pathophysiology of COPD as described herein will identify novel therapeutic targets for intervening COPD

Collective impact of scrap, random breakdown, overtime and discontinuous issuing on batch production planning in a supply-chain environment

This research explores the collective impact of overtime, random breakdown, discontinuous issuing rule, and scrap on batch production planning in a supply-chain environment. In today’s global business environment, manufacturing firms encounter numerous operational challenges. Externally, they must promptly satisfy the customers’ various requests, while internally, they must cautiously manage several inevitable issues in the fabrication process. These issues might be concerned with scrap, random breakdown, etc. Resolving such issues is crucial for meeting the due dates of customers’ orders, adhering to the expected manufacturing schedules, product quality, and minimizing the total fabrication-transportation-inventory costs. The study develops a model to characterize the system’s features mentioned above and assist the manufacturers with batch fabrication planning. The model proposes a solution process with an algorithm seeking an optimal runtime for the system. Additionally, it gives a numerical illustration depicting the collective and individual impacts of these special features on the operating policy and other performance indices. This model and the research findings can facilitate manufacturers