The Effectiveness of Social Media-Enabled Patient Communities on Health Goal Attainment: An Approach of Survival Analysis

Health goal striving activities are a major part of the daily lives of those fighting chronic diseases. In this study, we are interested in understanding the effectiveness of social media-enabled online patient communities on the outcome of health goal striving endeavor - health goal attainment. Applying social cognitive theory, we study the antecedents of health goal attainment from the respects of social support and self-reflection in online patient communities. We apply Survival Analysis to a data set of patients’ interactions and their health goal progress from a leading online patient community. Our findings show that emotional social support can increase patients’ chance to achieve their goals while informational social support does not appear to be effective. In addition, health-related self-reflection increases online patients’ likelihood of goal attainment, but leisure-oriented self-reflection negatively affects the possibility

Germanium doping of Si substrates for improved device characteristics and yield

During the last decade the 300 mm Si wafer has been optimized and one is already studying 450 mm crystals and wafers. The increasing silicon crystal diameter shows two important trends with respect to substrate characteristics: the interstitial oxygen concentration is decreasing while the size of grown in voids (COP's) in vacancy-rich crystals is increasing. The first effect is due the suppression of melt movements by the use of magnetic fields leading to a more limited transport of oxygen to the crystal. This and the decreasing thermal budget of advanced device processing leads to reduced internal gettering capacity. The increasing COP size is due to the combination of decreasing pulling rate and thermal gradient leading to a decreased void nucleation and increased thermal budget for void growth. The effect of Ge doping in the range between 10(16) cm(-3) and 10(19) cm(-3) on both COP's and oxygen precipitation will be discussed

Transcriptomic and Metabolomic Data Reveal the Key Metabolic Pathways Affecting Streltzoviella insularis (Staudinger) (Lepidoptera: Cossidae) Larvae During Overwintering

Streltzoviella insularis (Staudinger) (Lepidoptera: Cossidae) is a woodboring insect feeding on Fraxinus pennsylvanica, Sophora japonica, and Ginkgo biloba, as well as many other species used for urban greening and plain afforestation in northern China, including the temperate north. There is also a risk that S. insularis could spread through the transportation of seedlings, thereby increasing urban greening costs. However, how S. insularis increases the cold tolerance then reduces it to survive winter temperature below 0°C remains unclear. In the transcriptomic of S. insularis, we identified three profiles (profile 25, 27, and 13) whose trends related to the cold tolerance. We detected 1,783 differentially expressed genes (in profile 25) and identified 522 genes enriched in the AMPK signaling pathway. The metabolome analysis identified 122 differential metabolites. We identified four co-pathways, among which “Glycerophospholipid metabolism” was the pathway most enriched in differentially expressed genes and differential metabolites. The AMPK signaling and glycerophospholipid metabolism pathways play key roles in the natural overwintering physiological process of S. insularis larvae

A Secure Hybrid Duplex Relay System with Joint Optimization of Finite Blocklength and Power

As mission-critical Internet of Things (MC-IoT) is expected to carry important and private information, its high quality of service (QoS) and high physical layer (PHY) security are indispensable. Nevertheless, most existing PHY security related work is built on the assumption of infinite blocklength, which is not applicable to finite blocklength (FBL) transmission, a typical scenario in MC-IoT such as factory automation. In this paper, we address the PHY security issue of a hybrid duplex relay aided MC-IoT system with FBL. Closed-form expressions for statistical secrecy throughput of full-duplex (FD) and half-duplex (HD) relay systems are derived, respectively, which are verified by numerical results. Based on the closed-form secrecy throughput, joint optimization of blocklength and transmission powers at source and relay is conducted for FD and HD relay systems, respectively. A hybrid duplex relaying scheme is also proposed by selecting the duplex mode with a higher achievable secrecy throughput. Numerical results show that, together with the hybrid relaying scheme, the proposed relay system with joint power allocation and blocklength adaptation, relay mode selection achieves much higher secrecy throughput over the conventional sole FD or HD mode relaying systems. Also, it is revealed that increasing blocklength or transmitting power may not always lead to a higher secrecy throughput and energy efficiency (EE)

STPrivacy: Spatio-Temporal Privacy-Preserving Action Recognition

Existing methods of privacy-preserving action recognition (PPAR) mainly focus on frame-level (spatial) privacy removal through 2D CNNs. Unfortunately, they have two major drawbacks. First, they may compromise temporal dynamics in input videos, which are critical for accurate action recognition. Second, they are vulnerable to practical attacking scenarios where attackers probe for privacy from an entire video rather than individual frames. To address these issues, we propose a novel framework STPrivacy to perform video-level PPAR. For the first time, we introduce vision Transformers into PPAR by treating a video as a tubelet sequence, and accordingly design two complementary mechanisms, i.e., sparsification and anonymization, to remove privacy from a spatio-temporal perspective. In specific, our privacy sparsification mechanism applies adaptive token selection to abandon action-irrelevant tubelets. Then, our anonymization mechanism implicitly manipulates the remaining action-tubelets to erase privacy in the embedding space through adversarial learning. These mechanisms provide significant advantages in terms of privacy preservation for human eyes and action-privacy trade-off adjustment during deployment. We additionally contribute the first two large-scale PPAR benchmarks, VP-HMDB51 and VP-UCF101, to the community. Extensive evaluations on them, as well as two other tasks, validate the effectiveness and generalization capability of our framework

Retinal microvasculature features in patients with migraine: a systematic review and meta-analysis

BackgroundMigraine is a central nervous system disorder involving neuronal and vascular factors. The brain has a close anatomical relationship with retinal vessels and similar regulatory processes, and the retinal vascular system is the only in vivo vessel that can be directly visualized, while optical coherence tomography angiography (OCTA) is an advanced retinal vascular imaging technique. In this study, OCTA was used to study the retinal vascular density (VD) and foveal avascular zone (FAZ) in migraine patients, which provided a theoretical basis for its use as a candidate for rapid and non-invasive diagnosis of migraine.MethodsPublished studies comparing retinal microvascular profiles between migraine patients and healthy controls were obtained by a comprehensive search of electronic databases. Nine studies were finally included, including 775 eyes (migraine group: 444 eyes, control group: 331 eyes). Pooled effect sizes were presented as standardized mean differences (SMDs) and 95% confidence intervals (CIs). Statistical analysis was performed using Review Manager software (version 5.30).ResultsThe combined results revealed that the superficial and deep macular whole enface VD (MWEVD) (superficial VD: SMD = −0.30, P = 0.0001; deep VD: SMD = −0.61, P = 0.02), superficial foveal VD (FVD) (SMD = −0.42, P = 0.03), deep parafoveal VD (PFVD) (SMD = −0.31, P = 0.002), and peripapillary VD (PVD) (SMD = −0.49, P = 0.002) were significantly reduced in migraine patients compared with healthy people. However, there was a significant increase in the area of the FAZ in migraine patients (SMD = 0.56, P < 0.0001).ConclusionMigraine patients are prone to retinal microcirculation disorders, such as decreased blood vessel density and increased avascular area in the fovea. This provides a theoretical basis for OCTA as a candidate for rapid, non-invasive diagnosis of migraine

PyPose: A Library for Robot Learning with Physics-based Optimization

Deep learning has had remarkable success in robotic perception, but its data-centric nature suffers when it comes to generalizing to ever-changing environments. By contrast, physics-based optimization generalizes better, but it does not perform as well in complicated tasks due to the lack of high-level semantic information and the reliance on manual parametric tuning. To take advantage of these two complementary worlds, we present PyPose: a robotics-oriented, PyTorch-based library that combines deep perceptual models with physics-based optimization techniques. Our design goal for PyPose is to make it user-friendly, efficient, and interpretable with a tidy and well-organized architecture. Using an imperative style interface, it can be easily integrated into real-world robotic applications. Besides, it supports parallel computing of any order gradients of Lie groups and Lie algebras and $2^{\text{nd}}$-order optimizers, such as trust region methods. Experiments show that PyPose achieves 3-20$\times$ speedup in computation compared to state-of-the-art libraries. To boost future research, we provide concrete examples across several fields of robotics, including SLAM, inertial navigation, planning, and control