An Efficient Patch Dissemination Strategy for Mobile Networks

Mobile phones and personal digital assistants are becoming increasingly important in our daily life since they enable us to access a large variety of ubiquitous services. Mobile networks, formed by the connection of mobile devices following some relationships among mobile users, provide good platforms for mobile virus spread. Quick and efficient security patch dissemination strategy is necessary for the update of antivirus software so that it can detect mobile virus, especially the new virus under the wireless mobile network environment with limited bandwidth which is also large scale, decentralized, dynamically evolving, and of unknown network topology. In this paper, we propose an efficient semi autonomy-oriented computing (SAOC) based patch dissemination strategy to restrain the mobile virus. In this strategy, some entities are deployed in a mobile network to search for mobile devices according to some specific rules and with the assistance of a center. Through experiments involving both real-world networks and dynamically evolving networks, we demonstrate that the proposed strategy can effectively send security patches to as many mobile devices as possible at a considerable speed and lower cost in the mobile network. It is a reasonable, effective, and secure method to reduce the damages mobile viruses may cause

Direct Regularization from Co-Registered Anatomical Images for MRI-Guided Near-Infrared Spectral Tomographic Image Reconstruction

Combining anatomical information from high resolution imaging modalities to guide near-infrared spectral tomography (NIRST) is an efficient strategy for improving the quality of the reconstructed spectral images. A new approach for incorporating image information directly into the inversion matrix regularization was examined using Direct Regularization from Images (DRI), which encodes the gray-scale data into the NIRST image reconstruction problem. This process has the benefit of eliminating user intervention such as image segmentation of distinct regions. Specifically, the Dynamic Contrast Enhanced Magnetic Resonance (DCE-MR) image intensity value differences within the anatomical image were used to implement an exponentially-weighted regularization function between the image pixels. The algorithm was validated using simulated reconstructions with noise, and the results showed that spatial resolution and robustness of the reconstructed images were significantly improved by appropriate choice of the regularization weight parameters. The proposed approach was also tested on in vivo breast data acquired in a recent clinical trial combining NIRST / MRI for cancer tumor characterization. Relative to the standard “no priors” diffuse recovery, the contrast of the tumor to the normal surrounding tissue increased from 2.4 to 3.6, and the difference between the tumor size segmented from DCE-MR images and reconstructed optical images decreased from 18% to 6%, while there was an overall decrease in surface artifacts

Optimization of Fluorescent Imaging in the Operating Room through Pulsed Acquisition and Gating to Ambient Background Cycling

The design of fluorescence imaging instruments for surgical guidance is rapidly evolving, and a key issue is to efficiently capture signals with high ambient room lighting. Here, we introduce a novel time-gated approach to fluorescence imaging synchronizing acquisition to the 120 Hz light of the room, with pulsed LED excitation and gated ICCD detection. It is shown that under bright ambient room light this technique allows for the detection of physiologically relevant nanomolar fluorophore concentrations, and in particular reduces the light fluctuations present from the room lights, making low concentration measurements more reliable. This is particularly relevant for the light bands near 700nm that are more dominated by ambient lights

Induced Pluripotent Stem Cells for Tissue-Engineered Skeletal Muscles

Skeletal muscle, which comprises a significant portion of the body, is responsible for vital functions such as movement, metabolism, and overall health. However, severe injuries often result in volumetric muscle loss (VML) and compromise the regenerative capacity of the muscle. Tissue-engineered muscles offer a potential solution to address lost or damaged muscle tissue, thereby restoring muscle function and improving patients’ quality of life. Induced pluripotent stem cells (iPSCs) have emerged as a valuable cell source for muscle tissue engineering due to their pluripotency and self-renewal capacity, enabling the construction of tissue-engineered artificial skeletal muscles with applications in transplantation, disease modelling, and bio-hybrid robots. Next-generation iPSC-based models have the potential to revolutionize drug discovery by offering personalized muscle cells for testing, reducing reliance on animal models. This review provides a comprehensive overview of iPSCs in tissue-engineered artificial skeletal muscles, highlighting the advancements, applications, advantages, and challenges for clinical translation. We also discussed overcoming limitations and considerations in differentiation protocols, characterization methods, large-scale production, and translational regulations. By tackling these challenges, iPSCs can unlock transformative advancements in muscle tissue engineering and therapeutic interventions for the future

Multiobjective Guided Priors Improve the Accuracy of Near-Infrared Spectral Tomography for Breast Imaging

An image reconstruction regularization approach for magnetic resonance imaging-guided near-infrared spectral tomography has been developed to improve quantification of total hemoglobin (HbT) and water. By combining prior information from dynamic contrast enhanced (DCE) and diffusion weighted (DW) MR images, the absolute bias errors of HbT and water in the tumor were reduced by 22% and 18%, 21% and 6%, and 10% and 11%, compared to that in the no-prior, DCE- or DW-guided reconstructed images in three-dimensional simulations, respectively. In addition, the apparent contrast values of HbT and water were increased in patient image reconstruction from 1.4 and 1.4 (DCE) or 1.8 and 1.4 (DW) to 4.6 and 1.6