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IntroductionNorovirus is widely recognized as a leading cause of both sporadic cases and outbreaks of acute gastroenteritis (AGE) across all age groups. The GII.4 Sydney 2012 variant has consistently prevailed since 2012, distinguishing itself from other variants that typically circulate for a period of 2–4 years.ObjectiveThis review aims to systematically summarize the prevalence of norovirus gastroenteritis following emergence of the GII.4 Sydney 2012 variant.MethodsData were collected from PubMed, Embase, Web of Science, and Cochrane databases spanning the period between January 2012 and August 2022. A meta-analysis was conducted to investigate the global prevalence and distribution patterns of norovirus gastroenteritis from 2012 to 2022.ResultsThe global pooled prevalence of norovirus gastroenteritis was determined to be 19.04% (16.66–21.42%) based on a comprehensive analysis of 70 studies, which included a total of 85,798 sporadic cases with acute gastroenteritis and identified 15,089 positive cases for norovirus. The prevalence rate is higher in winter than other seasons, and there are great differences among countries and age groups. The pooled attack rate of norovirus infection is estimated to be 36.89% (95% CI, 36.24–37.55%), based on a sample of 6,992 individuals who tested positive for norovirus out of a total population of 17,958 individuals exposed during outbreak events.ConclusionThe global prevalence of norovirus gastroenteritis is always high, necessitating an increased emphasis on prevention and control strategies with vaccine development for this infectious disease, particularly among the children under 5 years old and the geriatric population (individuals over 60 years old).

China is moving forward, but it pays much attention to data analysis of infinite resource circulation. Therefore, this paper investigates the time-domain convolutional calculation method of deep learning and recurrent calculation method of deep learning and uses them to study and analyze the obstacles and countermeasures for the share of renewable energy in our country’s right grid. Then, the passing situation of renewable energy in China is analyzed. Information related to China’s advancement and utilization of inexhaustible resources from 2010 to 2020. From the analysis of the gathered information, it is unequivocal that the scale and share of inexhaustible resources of ancestors in our country’s rights are gradually increasing. Space occupancy in recent 3 years of inexhaustible resources generation in our country will be more than 133 million kilowatts, and the proportion is about 70% of our country’s right power supply; the solar power generation capacity will increase from almost nothing to 261.1 billion kilowatt-hours in 2020 from less than 300 million kilowatt-hours in 2010, which is nearly exponential growth. Finally, this paper combines the existing features of renewable energy in China, puts forward the problems and challenges encountered in the advancement of inexhaustible resources, and gives countermeasures that can be strengthened the utilization rate of renewable energy in the power grid.

The increasing use of automation in fishing vessels has improved trawling efficiency while directly affecting the fishing capacity and cost of fishing vessels. Among the various influencing factors, warp tension and warp length can be varied to automatically balance the retraction and release of warp control. We combined the two parameters and independently designed and developed the key equipment for fishing vessels—the warp dynamometer and meter counter—and control software. The accuracy of the warp tension and length measurements was improved. The designed equipment was applied to sea trials under different working conditions, and the test data records were exported. Next, filtered time-domain graphs of the required parameters were plotted through complex Fourier transform, first-order low-pass filtering, and inverse Fourier transform. The results of data processing using various parameters were compared and analysed to determine the variation trends of the parameters and verify the effects of their balance control. The results indicated that using an automatic balance control system that combines warp tension and warp length can be effective for the fishing operation of offshore double-deck trawlers. In addition, first-order low-pass filtering can be used to filter complex warp tension data. This study also determined the relationship between warp tension and experimental parameters such as warp length and ship speed during the release of control. After the balance control of warp tension and warp length, the net mouth area increased by 30.7% and 36.5%, respectively, and the fishing efficiency of the vessel improved considerably.

Wastewater and pollutants emitted from cotton fabric production have generated several impacts on the ecosystem and human health. The Environmental Profit and Loss (EP&L) methodology was proposed to assess the environmental performance of a business by converting various environmental impacts into social marginal cost (SMC). This study applied the EP&L method to calculate the SMC of 1,000 kg of knit cotton T-shirts from the knit-yarn production to the end-of-life stage. The results show that the highest SMC was that of greenhouse gas emissions, followed by water pollution and water use which were $40.2, $28.3, and $0.04, respectively. In terms of production processes, the SMC of batch dyeing was the highest, and compaction was the stage with the least SMC. Through analysis of results, the SMC of cotton T-shirt was found to be closely related to the production activities of enterprises and the use of consumers. Findings of this study are of practical importance and can be used as a reference for green production of cotton products.

Concentration field reconstruction (CFR) refers to the use of the collected spatio-temporal discrete concentration data to reconstruct the concentration field that can reflect the spatio-temporal distribution of pollutants according to certain rules, which is of great significance to ensure the safety of indoor environment. In this paper, using alcohol as the release source, and the field reconstruction experiment based on mobile robot is carried out in an environmental chamber with two types of ventilation: side-up-supply-and-side-down-return, and top-supply-and-side-down-return. Using the experimental data, the performance of Kernel DM+V/W+ method is compared with the other two internationally recognized Kernel DM+V method and Kernel DM+V/W method in field reconstruction and source location from the perspective of qualitative and quantitative. The comparison results show that the Kernel DM+V/W+ method not only has better field reconstruction performance, but also has better source localization performance.

To solve the problem of pollutant source localization in an indoor environment with dynamic mechanical ventilation better, this paper designed and built a 3D source localization system composed of three 3D source localization robots whose sensors can move under control in the height direction (0.5 m–1.5 m). Through adopting the 3D source localization system, we realized the application of the previously developed the improved whale optimization algorithm (IWOA) method in 3D source localization and proposed the 3D_IWOA method. To validate the feasibility of the 3D_IWOA method and compare the performance of the 3D_IWOA method and other three 3D source localization methods (the 3D_SPSO, 3D_WUⅡ, and 3D_IPSO methods), each method repeated 15 independent experiments in a Training-Center under the same conditions, respectively. For locating the periodic source at a height of 1.05 m in the downwind zone of this environment, the numbers of successful experiments of the 3D_SPSO, 3D_WUⅡ, 3D_IPSO, and 3D_IWOA methods were 5, 6, 11, and 13 (the success rates were 33.3%, 40.0%, 73.3%, and 86.7%), respectively. In addition, the means of total steps of the 3D_SPSO, 3D_WUⅡ, 3D_IPSO, and 3D_IWOA methods were 36.29 steps, 35.96 steps, 31.75 steps, and 38.15 steps, respectively.

The purpose of this paper is to provide a new method for solving the problem of the 3D source localization in indoor environments with weak airflow by the experimental study on the multi-robot method. For this purpose, we developed a 3D MRO (mobile robot olfaction) system consisting of three mobile robots. The gas sensor carried with each robot has a moving range of 0.5 m to 1.5 m on the Z-axis. A total of 60 experiments were conducted to validate and compare the standard whale optimization algorithm (SWOA) and the standard particle swarm optimization (SPSO) methods in a 7.65 m×4.1 m experimental area with two source heights (0.75 m and 1.05 m). For two source heights, the success rate and localization step of the SPSO method are 56.7% (17/30) and 31.4 steps, respectively. In addition, the success rate and localization step of the SWOA method are 80% (24/30) and 32.9 steps, respectively. These results show that the SWOA method has strong application potential in indoor environments with weak airflow.

The prediction of contaminant distribution in multi-zone environment is critical for ensuring indoor personnel health and making an optimistic ventilation strategy. However, the input of uncertainty parameters (flow coefficients, flow exponents, etc.) has a significant impact on the predicted pollutant concentrations. In this study, we proposed a reconstruction method to achieve parameter estimation for the multi-zone model. MATLAB codes was programmed to call CONTAM engine to accomplish pollutant transport simulation in a multi-zone scaled building model. Then a Bayesian inference algorithm compiled in MATLAB codes was applied to determine the unknown parameters iteratively. Finally, multi-zone scaled experiments with different forms of pollutant sources were employed to validate the reconstruction method. The results showed that the predicted concentrations with the reconstructed parameters agreed well with the measured data in the constant source (CS) experiment. While, for the dynamic source (DS) experiment, the predicted concentrations had some discrepancies with the measured data.

Since the postfire safety of prestressed RPC beams after exposure to elevated temperatures needs to be studied and proved, this paper prepares eight smart prestressed RPC beams with intelligent sensors built in to monitor the internal temperature, force, and strain. The residual bearing tests after fire are carried out. The failure process of the beams under static load with different fire durations cover thickness of tendons, load ratio, bonded and unbonded tendons, and partial prestressing ratio, which are investigated. The load-deflection curves, crack distributions and developments, and strain variations are obtained, in addition to the damage mechanism and failure mode of the beams. The results show that the load-deflection curve of the prestressed RPC beam after fire has obviously three polylines, and the deflection points are where the cracks expand and the tendons yield. The failure procedure is the same as that of under-reinforced beams, while the height of the crushing zone is much lower than that of the balanced-reinforced beam at room temperature. The whole span deformation demonstrates a strong catenary effect, and the midspan deflection is approximately 1/40 of the effective span. The postfire safety of the bonded prestressed RPC beams is superior to that of unbonded prestressed RPC beams. The test results of this paper provide a basis for the safety performance evaluation and control of prestressed RPC beams after fire.

In this paper we consider two important objects of transportation, cost and customer satisfaction. The latter mainly depends on vehicle arrival time and expecting time of the customer. Whereas in the reality, road conditions varies at different time periods and affect the vehicle travelling speed. Meanwhile, transport cost, including fuel consumption, relate to load of vehicle. Correspondingly, mathematical model of vehicle routing problem with soft time windows and road factor (VRPSTWRF) was established in which transport cost, fuel consumption and customer satisfaction are considered. Multi-agent ant colony optimization is proposed in which the features of agent perceiving and reacting to the environment are applied reasonably. Adaptive information heuristic factor and pheromone expectation heuristic factor changing mechanism is used to improve global convergence ability. Pheromone is updated adaptively, the fuel consumption rate also considered, to ensure the convergence speed. 3-opt strategy was introduced to improve local search ability. Thus, multi-agent ant colony optimization (MACO) was constructed and used to solve 40-customer VRPSTWRF model. Experiments show that MACO proposed is feasible and valid.