Skeleton-Based Activity Recognition for Process-Based Quality Control of Concealed Work via Spatial-Temporal Graph Convolutional Networks.

Computer vision (CV)-based recognition approaches have accelerated the automation of safety and progress monitoring on construction sites. However, limited studies have explored its application in process-based quality control of construction works, especially for concealed work. In this study, a framework is developed to facilitate process-based quality control utilizing Spatial-Temporal Graph Convolutional Networks (ST-GCNs).

Measuring Labor Input: Construction Activity Counting Using IMU on Hand Tools.

Efficient measurement of labor input is a critical aspect of on-site control and management in construction projects, as labor input serves as the primary and direct determinant of project outcomes. However, conventional manual inspection methods are off-line, tedious, and fail to capture their effectiveness. To address this issue, this research presents a novel method that leverages Inertial Measurement Unit (IMU) sensors attached to hand tools during construction activities to measure labor input in a timely and precise manner.

Feasibility Analysis of Using Channel State Information (CSI) Acquired from Wi-Fi Routers for Construction Worker Fall Detection.

Accidental falls represent a major cause of fatal injuries for construction workers. Failure to seek medical attention after a fall can significantly increase the risk of death for construction workers. Wearable sensors, computer vision, and manual techniques are common modalities for detecting worker falls in the literature.

Regulating intracellular ROS signal by a dual pH/reducing-responsive nanogels system promotes tumor cell apoptosis.

The levels of reactive oxygen species (ROS) in tumor cells are much higher than that in normal cells, and rise rapidly under the influence of exogenous or endogenous inducing factors, eventually leading to the apoptosis of tumor cells. Therefore, this study prepared a dual pH/reducing-responsive poly (-isopropylacrylamide-co-Cinnamaldehyde-co-D-α-tocopheryl polyethylene glycol 1000 succinate, PNCT) nanogels, which employed two exogenous ROS inducers, cinnamaldehyde (CA) and D-α-tocopheryl polyethylene glycol 1000 succinate (TPGS), to selectively induce apoptosis by regulating ROS levels in tumor cells. The PNCT nanogels were prepared by the free radical precipitation polymerization under the crosslink between pH-sensitive hydrazone and reducing-sensitive disulfide bonds, followed by the physicochemical and morphological characteristics investigations.