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The utilization of metamaterials plays a pivotal role in integrated photonics. The precise design of metamaterials enables them to finely manipulate light, resulting in an ultra-compact footprint and exceptional performance that cannot be achieved by traditional structures. The conventional methods for metamaterial design, however, encounter challenges from intricate targets. Although attempts have been made to apply inverse design to metamaterials, there is still a need for a highly intelligent, low-computation method, and easy-to-fabricate metamaterial structure. Here, we present an efficient methodology that combines metamaterials, heuristic algorithms, and machine learning to facilitate the rapid development of intricate devices. The method is used to design 1 × N power splitters with arbitrary power ratios, as an application example. Specifically, 1 × 2, 1 × 3, 1 × 4 power splitters with arbitrary ratios are fabricated and experimentally demonstrated. The application of this method in arbitrary power splitter highlights its appropriateness for the design and optimization within integrated photonics devices.

Chloramphenicol is a widely used bactericide and highly effective antibiotic in aquaculture and livestock breeding. To protect human health, detecting chloramphenicol residues in animal-derived food products has become increasingly important. This review introduces the properties of chloramphenicol, the limit standards, and the hazards of residual chloramphenicol in animal-derived food products. Furthermore, it describes commonly used chloramphenicol detection methods. In addition, the review thoroughly analyzes and summarizes the advantages and disadvantages of different detection methods, outlining methods to improve the efficiency and precision of chloramphenicol detection to ensure the quality and safety of animal-derived food products. Finally, the prospects for developing advanced detection techniques and analytical methods are prospected.

Purpose: The aim of this study was to evaluate the role of Pi10 in patients with fibrotic interstitial lung abnormality (fibrotic ILA) in a chest CT, according to cumulative cigarette smoking. Methods: We retrospectively assessed 54 fibrotic ILA patients and 18 healthy non-smokers (control) who underwent non-enhanced CT and pulmonary function tests. We quantitatively analyzed airway changes (the inner luminal area, airway inner parameter, airway wall thickness, Pi10, skewness, and kurtosis) in the chest CT of fibrotic ILA patients, and the fibrotic ILA patients were categorized into groups based on pack-years: light, moderate, heavy. Airway change data and pulmonary function tests among the three groups of fibrotic ILA patients were compared with those of the control group by one-way ANOVA. Results: Mean skewness (2.58 ± 0.36) and kurtosis (7.64 ± 2.36) in the control group were significantly different from those of the fibrotic ILA patients (1.89 ± 0.37 and 3.62 ± 1.70, respectively, p < 0.001). In fibrotic ILA group, only heavy smokers had significantly increased Pi10 (mean increase 0.04, p = 0.013), increased airway wall thickness of the segmental bronchi (mean increase 0.06 mm, p = 0.005), and decreased lung diffusing capacity for carbon monoxide (p = 0.023). Conclusion: Pi10, as a biomaker of quantitative CT in fibrotic ILA patients, can reveal that smoking affects airway remodeling.

The projection of surface runoff in the context of climate change is important to the rational utilization and distribution of water resources. This study did a case study in regions above Danjiangkou in Hanjiang River Basin. A basin scale hydrological model was built based on macroscale processes of surface runoff and water-energy balance. This model can describe the quantity relationship among climatic factors, underlying surface and surface runoff. Driven by hypothetical climatic scenarios and climate change dataset coming from CMIP5, the climate change impacts on surface runoff in the regions above Danjiangkou in Hanjiang River Basin can be addressed. The results showed that: (1) Compared with other distributed hydrological models, the hydrological model in this study has fewer parameters and simpler calculation methods. The model was good at simulating annual surface runoff. (2) The surface runoff was less sensitivity to climate change in the regions above Danjiangkou in Hanjiang River Basin. A 1°C increase in temperature might results in a surface runoff decrease of 2~5% and a 10% precipitation increase might result in a streamflow increase of 14~17%. (3) The temperature across the Fu River Basin were projected to increase by 1.4~2.3°C in 1961 to 1990 compared with that in 1961 to 1990. But the uncertainty existed among the projection results of precipitation. The surface runoff was excepted to decrease by 1.3~23.9% without considering the climate change projected by NorESM1-M and MIROC-ESM-CHEM, which was much different from other GCMs.

Taking the source region of the Yellow River as an example, this paper first introduces the theory of energy value and its basic steps. Then combined with the Yellow River source area, the variation characteristics of precipitation and surface water resources from 1961 to 2011 in the Yellow River source area were analyzed, and both of them showed a trend of decreasing year by year. On this basis, using the theory of energy value, combined with relevant parameters, taking 2011 year as an example, further analyses the chemical energy and solar energy of water resources in the Yellow River source area, and gives the value of surface water resources. The value of water resources per unit is 1.59 yuan/m3. For the Yellow River source area, the overall value of water resources for the whole basin in 2011 is 33.55 billion yuan. It can provide a reference for the analysis of the value of surface water resources in the Yellow River Basin.

The prediction of output power of wind farm has important value and significance to the normal operation of some large-scale wind power system. In this paper, the related prediction methods and practical application are studied, and the short-term power forecasting method of the wind power of the vector machine-Markov chain is proposed.