Objective: Cow's milk allergy (CMA) is a common allergic disease. Probiotics have been suggested as a treatment for CMA, with Lactobacillus rhamnosus GG (LGG) being one of the important predominant choices. Despite reports on this topic, the effectiveness of application in CMA remains to be firmly established.Methods: To assess the effects of LGG on CMA in children, the PubMed/Medline, Embase, Cochrane Library, and Web of Science databases were searched for studies on LGG in treatment of CMA, which were published in the English language.Results: Ten studies were finally included. Significantly higher tolerability rates favoring LGG over controls were observed [risk ratio (RR), 2.22; 95% confidence interval (CI), 1.86–2.66; I2 = 0.00; moderate-quality evidence]. There were no significant differences in SCORAD values favoring LGG over the placebo (mean difference, 1.41; 95% CI, −4.99–7.82; p = 0.67; very low-quality evidence), and LGG may have improved fecal occult blood (risk ratio, 0.36; 95% CI, 0.14–0.92; p = 0.03; low-quality evidence).Conclusion: We found that LGG may have moderate-quality evidence to promote oral tolerance in children with CMA and may facilitate recovery from intestinal symptoms. However, this finding must be treated with caution, and more gpowerful RCTs are needed to evaluate the most effective dose and treatment time for children with CMA.Registration number: CRD42021237221.

The target detection algorithms have the problems of low detection accuracy and susceptibility to occlusion in existing smart cities. In response to this phenomenon, this paper presents an algorithm for target detection in a smart city combined with depth learning and feature extraction. It proposes an adaptive strategy is introduced to optimize the algorithm search windows based on the traditional SSD algorithm, which according to the target operating conditions change, strengthening the algorithm to enhance the accuracy of the objective function which is combined with the weighted correlation feature fusion method, and this method is a combination of appearance depth features and depth features. Experimental results show that this algorithm has a better antiblocking ability and detection accuracy compared with the conventional SSD algorithms. In addition, it has better stability in a changing environment.

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Vehicle mobile Internet of Things uses sensor technology, mobile Internet technology, and intelligent computing technology to effectively monitor and provide comprehensive services for vehicle operation status. It is an important part of building a smart city, making urban transportation more efficient, environmentally friendly, intelligent, and safety. In the vehicle mobile Internet of Things, when in-vehicle sensors are in communication with each other, they are often affected by factors, such as network mobility, transmission range, and signal interference. Therefore, in order to ensure the continuity of communication between nodes and improve the quality of network communication, this paper proposes a vehicle mobile Internet of Things coverage enhancement algorithm (PANM). First, we derive the probabilistic analysis model of communication duration by analyzing the functional relationship of vehicle initial velocity, acceleration, spacing distance, and communication duration. Then, under the premise of ensuring the communication duration, in order to improve the coverage of the vehicle mobile Internet of Things, the network overlap ratio is introduced in the probability analysis model. Finally, we improve the network coverage performance of omnidirectional radiation and fan-shaped radiation communication models of vehicle mobile Internet of Things by limiting the overlap ratio threshold. The experimental simulation results indicate that the PANM algorithm can reduce the packet loss rate of the vehicle network and have a shorter communication delay.INDEX TERMS Vehicle mobile Internet of Things, communication duration, probability analysis, overlap ratio, network coverage enhancement algorithm. I. INTRODUCTIONCyber Physics System (CPS) is a multi-dimensional complex system integrating computing, network and physical environment. Vehicle mobile internet of things as one of the main research fields of CPS, has received the attention of many researchers in recent years. VMIT (Vehicle Mobile Internet of Things) is an overlay network established by a vehicle equipped with a remote communication device or a communication device with a certain sensing range [1], [2]. The VMIT can collect the data of the location of the vehicle and its surroundings and transmit the data to other vehicles, The associate editor coordinating the review of this manuscript and approving it for publication was Chunsheng Zhu.