To resolve the issues of a deep backbone network, a large model, slow reasoning speed on a mobile terminal, low detection accuracy for small targets and difficulties detecting and recognizing traffic lights in real time and accurately with YOLOv4, a traffic lights recognition method based on improved YOLOv4 is proposed. The lightweight ShuffleNetv2 network is utilized to replace the CSPDarkNet53 network of YOLOv4 to satisfy the requirements of a mobile terminal. The reformed k-means clustering algorithm is applied to generate anchor boxes for avoiding the sensitivity issue of outliers and initial values. A novel attention mechanism named CS2A is added to enhance the extraction capability of effective features. Multiple data augmentation methods are combined to improve the generalization ability of the model. Ultimately, the detection and recognition of traffic lights can be realized. The S2TLD dataset is selected for training and testing, and it can be proved that the recognition accuracy and model size are greatly optimized. Meanwhile, a self-made dataset is selected for training and testing. Compared with the conventional YOLOv4, the recognition accuracy of the proposed algorithm for traffic lights\' state information increases by 1.79%, and the model size decreases by 81.97%. Appropriate scenes are selected for real-vehicle testing and the results demonstrate that the detection speed of the presented algorithm increases by 16%, and the recognition effect for small targets increases by 37% in comparison with conventional YOLOv4.

UNASSIGNED: Chest compression depth (CCD) in cardiopulmonary resuscitation is important. However, lightweight rescuers have difficulty achieving an appropriate depth. Chest compression force (CCFORCE) can be increased by placing the arms at 100° to the patient\'s frontal plane. In a simulation manikin study, we compared the CCD at 90° and 100° among lightweight Asian females and hypothesized that the CCD would be greater when the arms were placed at 100°.
UNASSIGNED: We included 35 lightweight female students from Shimane University who performed compressions 30 times each at 90° and 100°. The CCFORCE and CCD and the residual force on the chest wall during decompression for each chest compression were compared using CPRmeter-2.
UNASSIGNED: Of the 35 participants, 3 were excluded because their angles deviated from the prescribed angle. Thirty-two participants were categorized according to CCD at 90°: ≤40 mm (group 1), 41-49 mm (group 2), and ≥ 50 mm (group 3). The overall mean CCD increased from 90° to 100° (44.3 ± 8.2 mm vs. 48.1 ± 7.2 mm; p < 0.05). The mean CCD changes between 90° and 100° were 34.4 ± 4.7 mm vs. 42.9 ± 4.8 mm (p < 0.05) in group 1, 44.9 ± 2.5 mm vs. 47.0 ± 4.2 mm (p = 0.17) in group 2, and 53.0 ± 2.7 mm vs. 55.4 ± 5.6 mm (p < 0.05) in group 3. The residual force was greater when the chest compression angle was 100°.
UNASSIGNED: CCD can be increased for lightweight rescuers when using a forward leaning position of 100° to the frontal plane of the patient. Further research is required to obtain more realistic situations.

The effects of cenospheres, an industrial waste residue, on the compressive strength, flexural strength, toughness, ductility, chemical component, microstructures, and micromechanics of lightweight toughness cement-based composites (LTCCs) by comprehensive experimental tests are explored in this paper. The results indicate that an increase in the amount of cenospheres leads to a decrease in the compressive and flexural strength of LTCCs. However, the specific strength of LTCCs increases with increasing cenosphere content. LTCCs containing 20% cenospheres and 1% fiber volume have the best toughness and ductility. Significant strain hardening occurs during the four-point bending and uniaxial tensile process. Furthermore, the incorporation of cenospheres promotes the hydration reaction of LTCCs due to its high pozzolanic activity. The LTCC cement paste has a low bonding strength to the fiber, which helps the fiber to be pulled out to produce greater bending deformation and tensile strain. The elastic modulus and hardness of the LTCC cement paste decrease linearly with increasing cenosphere content, which also causes the LTCC microstructure to become loose and more ettringite to generate. The weak interfacial transition zone between the cenospheres and the cement matrix is the important reason for the decreasing compressive strength of the LTCC. In conclusion, LTCC incorporating cenospheres is suitable for long-span steel deck pavements due to its light weight and excellent toughness. The successful application of cenospheres in engineering construction can save natural resources and contribute to sustainable development.

It has been shown that wood particleboards bonded with sour cassava starch can display low density combined with good physico-mechanical performance, thanks to starch being able to produce a strong foam that fills the interparticular space. Here we optimize the pressing conditions for the production of these panels. The procedure involved hot-plate pressing in two stages: (1) lowering the top platen to a specified thickness for a duration designated as pressing time, followed by (2) raising the top platen to allow panel expansion for a duration designated as hold time. The parameters studied were the pressing time (10 to 150 s), the hold time (290 to 890 s), and the top platen temperature (80 to 190 °C). The hold time and pressing time showed to be crucial parameters. The best operating conditions corresponded to 600 s of press cycle time, comprising 60 s of pressing time and 540 s of hold time. The top platen temperature used was 190 °C. The particleboards produced had a density of 405 kg·m-3, an internal bond strength of 0.44 N·mm-2, and a thickness swelling of 13.2%. This can be considered as very good performance, taking into account the panels\' low density.

The focus of this research was to design a functional and user-friendly reacher for people with spinal cord injuries (SCIs). Engineering advancements have taken assistive robotics to new dimensions. Technologies such as wheelchair robotics and myo-electronically controlled systems have opened up a wide range of new applications to assist people with physical disabilities. Similarly, exo-skeletal limbs and body suits have provided new foundations from which technologies can aid function. Unfortunately, these devices have issues of usability, weight, and discomfort with donning. The Smart Assistive Reacher Arm (SARA) system, developed in this research, is a voice-activated, lightweight, mobile device that can be used when needed. SARA was built to help overcome daily reach challenges faced by individuals with limited arm and hand movement capability, such as people with cervical level 5-6 (C5-6) SCI. This article shows that a functional reacher arm with voice control can be beneficial for this population. Comparison study with healthy participants and an SCI participant shows that, when using SARA, a person with SCI can perform simple reach and grasp tasks independently, without someone else\'s help. This suggests that the interface is intuitive and can be easily used to a high level of proficiency by a SCI individual.