Radiative metamaterials based on effective-medium theory

Thermal metamaterials have made significant advancements in the past few decades. However, the concept of thermal metamaterials is primarily rooted in the thermal conduction mechanism, which has consequently restricted their application scope. It is imperative to consider thermal radiation, another crucial thermal transport mechanism, particularly in high-temperature regimes, when designing thermal devices. In this review paper, we present the advancements in this area, with a specific focus on research conducted using the effective-medium theory. Additionally, we explore the potential applications of radiative thermal metamaterials and discuss prospective research directions from a microscopic perspective for future investigations

Distributed Outsourced Privacy-Preserving Gradient Descent Methods among Multiple Parties

The Internet of Things (IoT) is one of the latest internet evolutions. Cloud computing is an important technique which realizes the computational demand of largely distributed IoT devices/sensors by employing various machine learning models. Gradient descent methods are widely employed to find the optimal coefficients of a machine learning model in the cloud computing. Commonly, the data are distributed among multiple data owners, whereas the target function is held by the model owner. The model owner can train its model over data owner’s data and provide predictions. However, the dataset or the target function’s confidentiality may not be kept in secret during computations. Thus, security threats and privacy risks arise. To address the data and model’s privacy mentioned above, we present two new outsourced privacy-preserving gradient descent (OPPGD) method schemes over horizontally or vertically partitioned data among multiple parties, respectively. Compared to previously proposed solutions, our methods improve in comprehensiveness in a more general scene. The data privacy and the model privacy are preserved during the whole learning and prediction procedures. In addition, the execution performance evaluation demonstrates that our schemes can help the model owner to optimize its target function and provide exact prediction with high efficiency and accuracy

Effect of denosumab on glucose metabolism in postmenopausal osteoporotic women with prediabetes: a study protocol for a 12-month multicenter, open-label, randomized controlled trial

Abstract Background Participants with prediabetes are at a high risk of developing type 2 diabetes (T2D). Recent studies have suggested that blocking the receptor activator of nuclear factor-κB ligand (RANKL) may improve glucose metabolism and delay the development of T2D. However, the effect of denosumab, a fully human monoclonal antibody that inhibits RANKL, on glycemic parameters in the prediabetes population is uncertain. We aim to examine the effect of denosumab on glucose metabolism in postmenopausal women with osteoporosis and prediabetes. Methods This is a 12-month multicenter, open-label, randomized controlled trial involving postmenopausal women who have been diagnosed with both osteoporosis and prediabetes. Osteoporosis is defined by the World Health Organization (WHO) as a bone mineral density T score of ≤ − 2.5, as measured by dual-energy X-ray absorptiometry (DXA). Prediabetes is defined as (i) a fasting plasma glucose level of 100–125 mg/dL, (ii) a 2-hour plasma glucose level of 140–199 mg/dL, or (iii) a glycosylated hemoglobin A1c (HbA1c) level of 5.7–6.4%. A total of 346 eligible subjects will be randomly assigned in a 1:1 ratio to receive either subcutaneous denosumab 60 mg every 6 months or oral alendronate 70 mg every week for 12 months. The primary outcome is the change in HbA1c levels from baseline to 12 months. Secondary outcomes include changes in fasting and 2-hour blood glucose levels, serum insulin levels, C-peptide levels, and insulin sensitivity from baseline to 12 months, and the incidence of T2D at the end of the study. Follow-up visits will be scheduled at 3, 6, 9, and 12 months. Discussion This study aims to provide evidence on the efficacy of denosumab on glucose metabolism in postmenopausal women with osteoporosis and prediabetes. The results derived from this clinical trial may provide insight into the potential of denosumab in preventing T2D in high-risk populations. Trial registration This study had been registered in the Chinese Clinical Trials Registry. Registration number: ChiCTR2300070789 on April 23, 2023. https://www.chictr.org.cn