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In this study, hydrogen, hydroxyl, carbonyl, carboxyl, amine, epoxy functional groups are introduced into various pore structures of activated carbon, to investigate their effect on the adsorption of 4-chlorophenol by molecular simulation. Adsorption isotherm of 4-chlorophenol is then calculated by sing Grand Canonical Monte Carlo (GCMC) simulation. The simulation results showed that, on the none structure, the 4-chlorophenol adsorption capacity reached the maximum value with a pore size of 1.5 nm. In contrast, when a functional group is present on the surface, activated carbon with a 4 nm pore is more dominant in terms of adsorption capacity. All functional groups exert a great influence on the threshold pressure and reduce the adsorption capacity at high pressure. But at medium and low pressures, the adsorption capacity of activated carbon increases rapidly in the presence of functional groups. The simulation results also showed that the carboxyl functional group gives superior adsorption capacity at medium and low pressures. The ability of activated carbon to form adsorption bonds with 4-chlorophenol was further investigated by comparing the adsorption energy between them. It can be seen that the surface functionalization has provided additional information during the synthesis of carbon materials for the treatment of organic compounds.

Optical camera communication (OCC) is one of the most promising optical wireless technology communication systems. This technology has a number of benefits compared to radio frequency, including unlimited spectrum, no congestion due to high usage, and low operating costs. OCC operates in order to transmit an optical signal from a light-emitting diode (LED) and receive the signal with a camera. However, identifying, detecting, and extracting data in a complex area with very high mobility is the main challenge in operating the OCC. In this paper, we design and implement a real-time OCC system that can communicate in high mobility conditions, based on You Only Look Once version 8 (YOLOv8). We utilized an LED array that can be identified accurately and has an enhanced data transmission rate due to a greater number of source lights. Our system is validated in a highly mobile environment with camera movement speeds of up to 10 m/s at 2 m, achieving a bit error rate of 10−2. In addition, this system achieves high accuracy of the LED detection algorithm with mAP0.5 and mAP0.5:0.95 values of 0.995 and 0.8604, respectively. The proposed method has been tested in real time and achieves processing speeds up to 1.25 ms.

This paper presents a rolling shutter orthogonal frequency-division multiplexing (RS-OFDM) optical camera communication higher rate longer range proposed in IEEE 802.15.7a Task Group (TG7a) using an image sensor as a receiver. OFDM is a digital multi-carrier modulation scheme deployed for broadband wireless communication to resolve the inter-symbol interference (ISI) effect caused by the multipath channel. In optical wireless communication systems, OFDM was applied widely for indoor applications: internet of things, e-health, vehicular, and localization systems. The mobility scenario is a big problem for OWC systems, which reduces the system performance due to the optical channel variation in the processing time. In addition to that, signal detection should be considered in the mobility environment to improve the signal-to-noise ratio of OWC systems. In this paper, we proposed the convolution neural network (CNN) for LED detection in the RS-OFDM system, considering the mobility effect. In addition to that, the deep neural network was applied to detect the start of OFDM frame instead of conventional technology (Van De Beek algorithm). By applying our approach, the RS-OFDM system can achieve long communication (18 m distance) with a low error rate in the 2 m/s velocity environment.

Currently, wireless communication systems that use radio frequency are commonly deployed, for example, mobile communication systems, satellite systems, and the Internet of Things (IoT) systems. Based on their easy installation, wireless communication systems have benefits over other wired communication systems. However, using high frequencies to transfer data via wireless communication can hold significant risks for human health. Several researchers have studied this topic using visible light instead of Radio Frequency (RF) waveforms in communication systems. Many potential approaches are relevant in this regard, i.e., visible light communication, light fidelity, free-space optical, and optical camera communication. Artificial intelligence is also influencing the future of industry and people and is used to solve complex problems, create intelligent solutions, and replace human intelligence as the driving force behind emerging technologies such as big data, smart factories, and the IoT. In this paper, we proposed the architecture of the MIMO C-OOK (Multiple-Input Multiple-Output Camera On–Off Keying) scheme, which uses a convolutional neural network for light-emitting diode detection and a deep learning neural network for threshold predictions considering long-distance communication and mobility support. Our suggested method aimed to improve the performance of the traditional camera on–off keying scheme by increasing data rate, communication distance, and low bit error rate. Our suggested technique may achieve a communication distance of up to 22 m with a low error rate when considering the mobility impact (2 m/s, i.e., walking velocity) by controlling the exposure time, focal length, and employing Forward Error Correction code.

Objective: The purpose of this report is to describe a case series of children undergoing selective dorsal rhizotomy (SDR) for the treatment of spastic cerebral palsy in Vietnam. Also described is an international cooperation model to facilitate the development of a new, multidisciplinary team for the evaluation and treatment of these children., Methods: Details of international collaboration are described, including in-person travel and virtual interactions. All cases of children younger than 18 years undergoing SDR for treatment of spastic cerebral palsy at a single center in Hanoi, Vietnam are described, including preoperative evaluation of spasticity and gait as well as results at 6 and 12 months. Results are summarized using descriptive statistics., Results: Since the beginning of cooperation in training and transferring SDR techniques by experts from the United States, in the period from June 2016 to December 2022, 18 SDR surgeries were performed in Hanoi. Patients' ages ranged from 2 to 14 years; 13 were male and 5 were female. Overall, approximately 60% of nerve rootlets were cut. Modified Ashworth Scale scores at 6 and 12 months after surgery in the hip, knee, and ankle joints showed improvement from preoperative values. There were 2 recorded complications: intracranial hypotension causing subdural hemorrhage and a case of skin infection at the incision site., Conclusions: The ongoing international cooperation between Vietnamese and American physicians has helped improve the surgical treatment of spasticity in children with cerebral palsy in Hanoi, providing children with a surgical treatment option with successful outcomes., (Copyright © 2024 Elsevier Inc. All rights reserved.)