An archetypal determination of mobile cloud computing for emergency applications using decision tree algorithm.

Numerous users are experiencing unsafe communications due to the growth of big network mediums, where no node communication is detected in emergency scenarios. Many people find it difficult to communicate in emergency situations as a result of such communications. In this paper, a mobile cloud computing procedure is implemented in the suggested technique in order to prevent such circumstances, and to make the data transmission process more effective. An analytical framework that addresses five significant minimization and maximization objective functions is used to develop the projected model. Additionally, all mobile cloud computing nodes are designed with strong security, ensuring that all the resources are allocated appropriately. In order to isolate all the active functions, the analytical framework is coupled with a machine learning method known as Decision Tree. The suggested approach benefits society because all cloud nodes can extend their assistance in times of need at an affordable operating and maintenance cost. The efficacy of the proposed approach is tested in five scenarios, and the results of each scenario show that it is significantly more effective than current case studies on an average of 86%

ByteTrackV2: 2D and 3D Multi-Object Tracking by Associating Every Detection Box

Multi-object tracking (MOT) aims at estimating bounding boxes and identities of objects across video frames. Detection boxes serve as the basis of both 2D and 3D MOT. The inevitable changing of detection scores leads to object missing after tracking. We propose a hierarchical data association strategy to mine the true objects in low-score detection boxes, which alleviates the problems of object missing and fragmented trajectories. The simple and generic data association strategy shows effectiveness under both 2D and 3D settings. In 3D scenarios, it is much easier for the tracker to predict object velocities in the world coordinate. We propose a complementary motion prediction strategy that incorporates the detected velocities with a Kalman filter to address the problem of abrupt motion and short-term disappearing. ByteTrackV2 leads the nuScenes 3D MOT leaderboard in both camera (56.4% AMOTA) and LiDAR (70.1% AMOTA) modalities. Furthermore, it is nonparametric and can be integrated with various detectors, making it appealing in real applications. The source code is released at https://github.com/ifzhang/ByteTrack-V2.Comment: Code is available at https://github.com/ifzhang/ByteTrack-V2. arXiv admin note: text overlap with arXiv:2110.06864; substantial text overlap with arXiv:2203.06424 by other author

Endurance exercise is a leptin signaling mimetic in hypothalamus of Wistar rats

BACKGROUND: Endurance exercise is known to promote a substantial effect on the energy balance in rats and humans. However, little is known about the exact mechanisms for the appetite-suppressive effects of endurance exercise. We hypothesized that endurance training might activate signaling cascades in the hypothalamus known to be involved in leptin signaling. METHODS: 16 male Wistar rats were randomly assigned to two groups: sedentary (n = 8) and exercise groups (n = 8). Animals in the exercise group started treadmill running at 30 m/min, 0% grade, for 1 min/bout. Running time was gradually increased by 2 min/bout every day. The training plan was one bout per day during initial two weeks, and two bouts per day during 3rd-9th week. At the end of nine-week experiment, blood was analyzed for low-density lipoprotein cholesterol (LDL-C), triglyceride (TG), total cholesterol (TC), free fatty acid (FFA), interleukin (IL)-6, and leptin in both groups. Activations of janus kinase 2-signaling transducer and activator of transcription 3 (JAK2-STAT3), protein kinase B (Akt), extracellular regulated kninase (ERKs), and suppressor of cytokine signaling 3 (SOCS3) in hypothalamus were measured in the end of nine weeks of exercise protocol. RESULTS: Nine-week endurance exercise induced lower concentrations of LDL-C, TG, TC, FFA, and leptin in rats (P < 0.05 or P < 0.01). Nine-week endurance exercise significantly increased the circulating IL-6 concentration compared with sedentary group (239.6 ± 37.2 pg/ml vs. 151.8 ± 31.5 pg/ml, P < 0.01). Exercise rats showed significant increases in JAK2, STAT3, Akt, ERKs, and SOCS3 phosphorylations compared with sedentary rats (P < 0.01). CONCLUSION: The data suggest that endurance exercise is a leptin signaling mimetic in hypothalamus of Wistar rats

Outer-inner Dual Reinforced Micro/Nano Hierarchical Scaffolds for Promoting Osteogenesis

Biomimetic scaffolds have been extensively studied for guiding osteogenesis through structural cues. Inspired by the natural bone growth process, we have employed a hierarchical outer-inner dual reinforcing strategy, which relies on the interfacial ionic bond interaction between amine/calcium and carboxyl group, to build a nanofiber/particle dual strengthened hierarchical silk fibroin scaffold. The scaffold can provide applicable form of osteogenic structural cue and mimic the natural bone forming process. Owing to the active interaction between compositions located in the outer pore space and the inner pore wall, the scaffold has over 4 times improvement on mechanical property, followed by significant alteration on cell-scaffold interaction pattern, demonstrated by over 2 times’ elevation on the spreading area and enhanced osteogenic activity potentially involving activities of integrin, Vinculin and Yes-associated protein (YAP). In vivo performance of the scaffold identified the inherent osteogenic effect of structural cue, which promotes rapid and uniform regeneration. Overall, the hierarchical scaffold is promising in promoting uniform bone regeneration through its specific structural cue endowed by its micro-nano construction.Peer reviewe

A Synthetic Bandwidth Method for High-Resolution SAR Based on PGA in the Range Dimension

The synthetic bandwidth technique is an effective method to achieve ultra-high range resolution in an SAR system. There are mainly two challenges in its implementation. The first one is the estimation and compensation of system errors, such as the timing deviation and the amplitude-phase error. Due to precision limitation of the radar instrument, construction of the sub-band signals becomes much more complicated with these errors. The second challenge lies in the combination method, that is how to fit the sub-band signals together into a much wider bandwidth. In this paper, a novel synthetic bandwidth approach is presented. It considers two main errors of the multi-sub-band SAR system and compensates them by a two-order PGA (phase gradient auto-focus)-based method, named TRPGA. Furthermore, an improved cut-paste method is proposed to combine the signals in the frequency domain. It exploits the redundancy of errors and requires only a limited amount of data in the azimuth direction for error estimation. Moreover, the up-sampling operation can be avoided in the combination process. Imaging results based on both simulated and real data are presented to validate the proposed approach