An efficient catalytic system for the conversion of 5hydroxymethylfurfural (HMF) into N-containing compounds over low-cost non-noble-metal catalysts is preferable, but it is challenging to reach high conversion and selectivity under mild conditions. Herein, an Al 2 O 3 -supported carbon-doped Ni catalyst was obtained via the direct pyrolysis-reduction of a mixture of Ni 3 (BTC) 2 • 12H 2 O and Al 2 O 3 , generating stable Ni 0 species due to the presence of carbon residue. A high yield of 96 % was observed in the reductive amination of HMF into 5-hydroxymethyl furfurylamine (HMFA) with ammonia and hydrogen at ambient temperature. The catalyst was recyclable and could be applied to the ambient-temperature synthesis of HMFbased secondary/tertiary amines and other biomass-derived amines from the carbonyl compounds. The significant performance was attributable to the synergistic effect of Ni 0 species and acidic property of the support Al 2 O 3 , which promoted the selective ammonolysis of the imine intermediate while inhibiting the potential side reaction of over-hydrogenation.

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To overcome the shortcomings of conventional slope monitoring methods, this paper presented an in-place inclinometer based on BOTDR (Brillouin Optical Time Domain Reflectometer) which was used to obtain the long-term internal deformation in the slope. The installation process of optical fiber sensors and its measuring principle were introduced. The result of analysis indicated that the error in the measured displacement was proportional to the square of the inclinometer length and the precision of the BOTDR instrument, while it was inversely proportional to the diameter of the inclinometer tube. An actual field slope deformation monitoring case was also introduced. The results show that the BOTDR based inclinometer has a good consistency with the traditional inclinometer. It can effectively access the internal deformation of the slope and help to find the position of potential sliding surface accurately. This technology shows a high reliability and practicality in engineering application that will promote deeper research of slope in the future.

Human migration is responsible for forming modern civilization and has had an important influence on the development of various countries. There are many issues worth researching, and "the reason to move" is the most basic one. The concept of migration cost in the classical self-selection theory, which was introduced by Roy and Borjas, is useful. However, migration cost cannot address global migration because of the limitations of deterministic and bilateral choice. Following the idea of migration cost, this paper developed a new probabilistic multilateral migration model by introducing the Boltzmann factor from statistical physics. After characterizing the underlying mechanism or driving force of human mobility, we reveal some interesting facts that have provided a deeper understanding of international migration, such as the negative correlation between migration costs for emigrants and immigrants and a global classification with clear regional and economic characteristics, based on clustering of migration cost vectors. In addition, we deconstruct the migration barriers using regression analysis and find that the influencing factors are complicated but can be partly (12.5%) described by several macro indexes, such as the GDP growth of the destination country, the GNI per capita and the HDI of both the source and destination countries.In this globalization wave, the scale and diversity of international migration are increasing sustainably Considering immigrants as the research object, much work has been performed in this field. Aside from research on migration patterns 2-6 , the effects and consequences of international migration have intrigued many researchers. Researchers have discussed the social and economic influence of migration on the origin and destination countries. Generally, the migration of skilled workers benefits destination countries, but the effect on the origin countries is controversial. Some researchers hold that migration is harmful to the origin countries [7][8][9][10] . However, other researchers have identified the potential benefits of brain drain or brain gain [11][12][13][14][15][16][17][18][19] . Although different opinions exist, most studies have acknowledged the importance of migration flows to both the origin and destination countries. Other works have focused on the complex effective factors of human migration. However, most studies use qualitative analyses without quantification. This is because migration is a complex field of research that includes topics from a wide range of fields, such as development, trade, fiscal studies, demography, policy, and human resources 20 . So far, the quantitative analysis and estimation of the factors affecting migration patterns have remained on the research frontier. The reasons for migration are basic and critical; establishing those reasons would help to explain the current circumstances of international migration, predict the evolution of migration patterns, and even design more beneficial migration policies.In quantitative analysis and esti...

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By installing FBG sensors on the geogrids, smart geogrids can both reinforce and monitor the stability for geogrid-reinforced slopes. In this paper, a geogrid-reinforced sand slope model test is conducted in the laboratory and fiber Bragg grating (FBG) sensing technology is used to measure the strain distribution of the geogrid. Based on the model test, the performance of the reinforced soil slope is simulated by finite element software Midas-GTS, and the stability of the reinforced soil slope is analyzed by strength reduction method. The relationship between the geogrid strain and the factor of safety is set up. The results indicate that the measured strain and calculated results agree very well. The geogrid strain measured by FBG sensor can be applied to evaluate the stability of geogrid-reinforced sand slopes.

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The formation and growth of cracks in concrete dams are mainly induced by hydrostatic and temperature loads. As cracks especially unstable cracks are of great danger to the safety of dams, it is critical to avoid extremely adverse load combinations during the dam operations to achieve the stability of cracks. Conventionally, the adverse load combinations have to be determined empirically by experts based on specific dam site conditions. Therefore, it is attractive to apply quantitative instead of empirical methods to identify the adverse loading conditions. In this study, we employ an adaptive neuro-fuzzy inference system (ANFIS) to Chencun concrete dam. The ANFIS is able to help us build a relationship between the model inputs (reservoir water level and air temperature) and the model output (crack opening displacement). Based on this relationship, the rules of the adverse load combinations to the crack are generated directly from the monitoring data. The accuracy of the trained ANFIS is proved by comparing the modeling results and the monitoring data. Our work demonstrates that the ANFIS is a useful approach for accurately recognizing the rules of the adverse load combinations that can be used in the knowledge base of dam safety expert system. crack, concrete dam, load combination, adaptive neuro-fuzzy inference system, rules Citation:Xu H Z, Li X H. Inferring rules for adverse load combinations to crack in concrete dam from monitoring data using adaptive neuro-fuzzy inference system.