Design and Testing of Real-Time Sensing System Used in Predicting the Leakage of Subsea Pipeline.

This study integrates the array sensing module and the flow leakage algorithm. In this study, a real-time monitoring deep-sea pipeline damage sensing system is designed to provide decision-making parameters such as damage coordinates and damage area. The array sensor module is composed of multiple YF-S201 hall sensors and controllers.

A Self-Powered Strain Sensor Applied to Real-Time Monitoring for Movable Structures.

This study uses near-field electrospinning (NFES) technology to make a novel self-powered strain sensor and applies it to the real-time monitoring of a bending structure, so that the measurement equipment can be reduced in volume. A self-powered strain sensor consists of polyvinylidene difluoride (PVDF) fibers, a PDMS fixed substrate, and an aluminum electrode. PVDF fibers are spun with DMSO and acetone using NFES technology, with a diameter of about 8 μm, Young's modulus of 1.

New Insights Into Drug Repurposing for COVID-19 Using Deep Learning.

The coronavirus disease 2019 (COVID-19) has continued to spread worldwide since late 2019. To expedite the process of providing treatment to those who have contracted the disease and to ensure the accessibility of effective drugs, numerous strategies have been implemented to find potential anti-COVID-19 drugs in a short span of time. Motivated by this critical global challenge, in this review, we detail approaches that have been used for drug repurposing for COVID-19 and suggest improvements to the existing deep learning (DL) approach to identify and repurpose drugs to treat this complex disease.

Prediction of drug adverse events using deep learning in pharmaceutical discovery.

Traditional machine learning methods used to detect the side effects of drugs pose significant challenges as feature engineering processes are labor-intensive, expert-dependent, time-consuming and cost-ineffective. Moreover, these methods only focus on detecting the association between drugs and their side effects or classifying drug-drug interaction. Motivated by technological advancements and the availability of big data, we provide a review on the detection and classification of side effects using deep learning approaches.

Machine learning on adverse drug reactions for pharmacovigilance.

Machine learning, especially deep learning, has the predictive power to predict adverse drug reactions, repurpose drugs and perform precision medicine. We provide a background of machine learning and propose a potential high-performance deep learning framework for its successful applications in these practices.

Extending the Lifespan of Soluble Lead Flow Batteries with a Sodium Acetate Additive.

In this report, we present a method for the construction of a soluble lead flow battery (SLFB) with an extended cycle life. By supplying an adequate amount of sodium acetate (NaOAc) to the electrolyte, a cycle life extension of over 50% is demonstrated for SLFBs via long-term galvanostatic charge/discharge experiments. A higher quality of the PbO2 electrodeposit at the positive electrode is quantitatively validated for NaOAc-added electrolyte by throwing index (TI) measurements.

AgSnS: a new IR solar absorber material with a near optimal bandgap.

We report the synthesis and photovoltaic properties of a new ternary solar absorber - AgSnS nanocrystals prepared by successive ionic layer adsorption reaction (SILAR) technique. The synthesized AgSnS nanocrystals have a bandgap of 1.24-1.

Post-injury treatment with 7,8-dihydroxyflavone, a TrkB receptor agonist, protects against experimental traumatic brain injury via PI3K/Akt signaling.

Tropomyosin-related kinase B (TrkB) signaling is critical for promoting neuronal survival following brain damage. The present study investigated the effects and underlying mechanisms of TrkB activation by the TrkB agonist 7,8-dihydroxyflavone (7,8-DHF) on traumatic brain injury (TBI). Mice subjected to controlled cortical impact received intraperitoneal 7,8-DHF or vehicle injection 10 min post-injury and subsequently daily for 3 days.

Correction: Wogonin Improves Histological and Functional Outcomes, and Reduces Activation of TLR4/NF-κB Signaling after Experimental Traumatic Brain Injury.

[This corrects the article DOI: 10.1371/journal.pone.

Wogonin improves histological and functional outcomes, and reduces activation of TLR4/NF-κB signaling after experimental traumatic brain injury.

Background: Traumatic brain injury (TBI) initiates a neuroinflammatory cascade that contributes to neuronal damage and behavioral impairment. This study was undertaken to investigate the effects of wogonin, a flavonoid with potent anti-inflammatory properties, on functional and histological outcomes, brain edema, and toll-like receptor 4 (TLR4)- and nuclear factor kappa B (NF-κB)-related signaling pathways in mice following TBI.

Methodology/principal Findings: Mice subjected to controlled cortical impact injury were injected with wogonin (20, 40, or 50 mg·kg(-1)) or vehicle 10 min after injury.