Secrecy performance of TAS/SC-based multi-hop harvest-to-transmit cognitive WSNs under joint constraint of interference and hardware imperfection

In this paper, we evaluate the secrecy performance of multi-hop cognitive wireless sensor networks (WSNs). In the secondary network, a source transmits its data to a destination via the multi-hop relaying model using the transmit antenna selection (TAS)/selection combining (SC) technique at each hop, in the presence of an eavesdropper who wants to receive the data illegally. The secondary transmitters, including the source and intermediate relays, have to harvest energy from radio-frequency signals of a power beacon for transmitting the source data. Moreover, their transmit power must be adjusted to satisfy the quality of service (QoS) of the primary network. Under the joint impact of hardware imperfection and interference constraint, expressions for the transmit power for the secondary transmitters are derived. We also derive exact and asymptotic expressions of secrecy outage probability (SOP) and probability of non-zero secrecy capacity (PNSC) for the proposed protocol over Rayleigh fading channel. The derivations are then verified by Monte Carlo simulations.Web of Science195art. no. 116

Environmental allergen reduction in asthma management: an overview

Asthma is a prevalent non-communicable disease that affects both children and adults. Many patients with severe, uncontrolled asthma could not achieve total control despite using anti-asthmatic drugs. There is increasing evidence that allergy to environmental allergens, including both indoor and outdoor allergens, is associated with asthma symptoms and severe asthma. Frequently reported sensitized allergens were dust mites, cockroaches, grass pollens, molds, pets, and rodents in allergic asthma patients, although the patterns of widespread allergens differed from each country. Allergen avoidance is the cornerstone of asthma management, especially in sensitized subjects. This review summarizes environmental allergen avoidance and clarifies their effects on asthma control. Despite contrasting results about the impact of allergen exposure reduction on asthma control, several studies supported the beneficial effects of reducing asthma-related symptoms or risk of exacerbations as a nondrug therapy. Identifying environmental allergens is helpful for asthma patients, and further studies on clinically effective avoidance methods are required

Inhibition of long chain fatty acyl-CoA synthetase (ACSL) and ischemia reperfusion injury

Various triacsin C analogs, containing different alkenyl chains and carboxylic acid bioisoteres including 4-aminobenzoic acid, isothiazolidine dioxide, hydroxylamine, hydroxytriazene, and oxadiazolidine dione, were synthesized and their inhibitions of long chain fatty acyl-CoA synthetase (ACSL) were examined. Two methods, a cell-based assay of ACSL activity and an in situ [¹⁴C]-palmitate incorporation into extractable lipids were used to study the inhibition. Using an in vivo leukocyte recruitment inhibition protocol, the translocation of one or more cell adhesion molecules from the cytoplasm to the plasma membrane on either the endothelium or leukocyte or both was inhibited by inhibitors 1, 9, and triacsin C. The results suggest that inhibition of ACSL may attenuate the vascular inflammatory component associated with ischemia reperfusion injury and lead to a decrease of infarct expansion

Multichannel Photon Counting Lidar Measurements Using USB-based Digital Storage Oscilloscope

We present a simple method of making multichannel photon counting measurements of weak lidar signal from large ranges, using commonly available USB-based digital storage oscilloscopes. The single photon pulses from compact photomultiplier tubes are amplified and stretched so that the pulses are large and broad enough to be sampled efficiently by the USB oscilloscopes. A software interface written in Labview is then used to count the number of photon pulses in each of the prescribed time bins to form the histogram of LIDAR signal. This method presents a flexible alternative to the modular multichannel scalers and facilitate the development of sensitive lidar systems

A comprehensive evaluation of polygenic score and genotype imputation performances of human SNP arrays in diverse populations

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On the Out of Distribution Robustness of Foundation Models in Medical Image Segmentation

Constructing a robust model that can effectively generalize to test samples under distribution shifts remains a significant challenge in the field of medical imaging. The foundational models for vision and language, pre-trained on extensive sets of natural image and text data, have emerged as a promising approach. It showcases impressive learning abilities across different tasks with the need for only a limited amount of annotated samples. While numerous techniques have focused on developing better fine-tuning strategies to adapt these models for specific domains, we instead examine their robustness to domain shifts in the medical image segmentation task. To this end, we compare the generalization performance to unseen domains of various pre-trained models after being fine-tuned on the same in-distribution dataset and show that foundation-based models enjoy better robustness than other architectures. From here, we further developed a new Bayesian uncertainty estimation for frozen models and used them as an indicator to characterize the model's performance on out-of-distribution (OOD) data, proving particularly beneficial for real-world applications. Our experiments not only reveal the limitations of current indicators like accuracy on the line or agreement on the line commonly used in natural image applications but also emphasize the promise of the introduced Bayesian uncertainty. Specifically, lower uncertainty predictions usually tend to higher out-of-distribution (OOD) performance.Comment: Advances in Neural Information Processing Systems (NeurIPS) 2023, Workshop on robustness of zero/few-shot learning in foundation model