ALBERT

Description: As one of the most destructive and costly natural disasters, drought has far-reaching negative effects on agriculture, water resources, the environment, and human life. Scientific understanding of propagation from meteorological to hydrological drought is of great significance for accurate forecasting of hydrological drought and preventing and mitigating drought disasters. The objective of this study is to analyze the spatio-temporal variational characteristics of propagation from meteorological drought to hydrological drought and the associated driving mechanisms in the eastern Qilian Mountains using the standard precipitation index (SPI), standardized runoff index (SRI), and drought propagation intensity index (DPI). The results show that there has been meteorological humidification and hydrological aridification in the upper reaches of the Shiyang River Basin over the last 56 years; especially in the 2000s, the intensity of hydrological drought was the strongest and the intensity of meteorological drought was the weakest, indicating the propagation intensity of meteorological drought to hydrological drought was extremely strong during this period. The changes of meteorological and hydrological dry–wet are different, both on seasonal and monthly scales. The meteorological dry–wet is shown to have had a significant effect both on the current and month-ahead hydrological dry–wet, where the one-month lag effect was most obvious. The relationship between meteorological and hydrological droughts also vary in space: Hydrological aridification in the Huangyang River, and the rivers east of it, was greater than that in the western tributaries. The drought propagation intensities from west to east showed a decreasing trend, excluding the Huangyang River. Climate and land-use changes are the main factors affecting the propagation from meteorological drought to hydrological drought. When the natural vegetation area accounted for between 76.3–78%, the cultivated land area between 0.55–3.6% and the construction area between 0.08–0.22% were a peer-to-peer propagation process from meteorological drought to hydrological drought in the upper reaches of the Shiyang River.

Description: The urban transport sector has become one of the major contributors to global CO2 emissions. This paper investigates the driving forces of changes in CO2 emissions from the passenger transport sectors in different cities, which is helpful for formulating effective carbon-reduction policies and strategies. The logarithmic mean Divisia index (LMDI) method is used to decompose the CO2 emissions changes into five driving determinants: Urbanization level, motorization level, mode structure, energy intensity, and energy mix. First, the urban transport CO2 emissions between 1960 and 2001 from 46 global cities are calculated. Then, the multiplicative decomposition results for megacities (London, New York, Paris, and Tokyo) are compared with those of other cities. Moreover, additive decomposition analyses of the 4 megacities are conducted to explore the driving forces of changes in CO2 emissions from the passenger transport sectors in these megacities between 1960 and 2001. Based on the decomposition results, some effective carbon-reduction strategies can be formulated for developing cities experiencing rapid urbanization and motorization. The main suggestions are as follows: (i) Rational land use, such as transit-oriented development, is a feasible way to control the trip distance per capita; (ii) fuel economy policies and standards formulated when there are oil crisis are effective ways to suppress the increase of CO2 emissions, and these changes should not be abandoned when oil prices fall; and (iii) cities with high population densities should focus on the development of public and non-motorized transport.

Description: An apparatus for the analysis of pressure cores containing gas hydrates at in situ pressures was designed, and a series of experiments to determine the compressional wave response of hydrate-bearing sands were performed systematically in the laboratory. Considering the difficulties encountered in performing valid laboratory tests and in recovering intact hydrate bearing sediment samples, the laboratory approach enabled closer study than the marine environment due to sample recovery problems. The apparatus was designed to achieve in situ hydrate formation in bearing sediments and synchronous ultrasonic detection. The P-wave velocity measurements enabled quick and successive ultrasonic analysis of pressure cores. The factors influencing P-wave velocity (Vp), including hydrate saturation and formation methodology, were investigated. By controlling the initial water saturation and gas pressure, we conducted separate experiments for different hydrate saturation values ranging from 2% to 60%. The measured P-wave velocity varied from less than 1700 m/s to more than 3100 m/s in this saturation range. The hydrate saturation can be successfully predicted by a linear fitting of the attenuation (Q−1) to the hydrate saturation. This approach provided a new method for acoustic measurement of the hydrate saturation when the arrival time of the first wave cannot be directly distinguished. Our results demonstrated that the specially designed non-embedded ultrasonic detection apparatus could determine the hydrate saturation and occurrence patterns in pressure cores, which could assist further hydrate resource exploration and detailed core analyses.

Description: Water pump control, prevalent in various industrial plants, such as wastewater treatment and steam generator facilities, plays a significant role in maintaining economic efficiency and stable plant operation. Due to its slow dynamics, strong nonlinearity, and various disturbances, it is also widely studied as a typical benchmark problem in process control. The current control strategies can be categorized into two aspects: one branch resorts to model-based design and the other to data-driven design. To merge the merits and overcome the deficiencies of each paradigm, this paper proposes a hybrid data-driven and model-assisted control strategy, namely modified active disturbance rejection control (MADRC). The model information regarding water dynamics is incorporated into an extended state observer (ESO), which is used to estimate and mitigate the limitations of slow dynamics, strong nonlinearity, and various disturbances by analyzing the real-time data. The tuning formula is given in terms of the desired closed-loop performance. It is shown that MADRC is able to produce a satisfactory control performance while maintaining a low sensitivity to the measurement noise under general parametric setting conditions. The simulation results verify the clear superiority of MADRC over the proportional-integral (PI) controller and the conventional ADRC, and the results also evidence its noise reduction effects. The experimental results agree well with the simulation results based on a water tank setup. The proposed MADRC approach is able to improve the control performance while reducing the actuator fluctuation. The results presented in this paper offer a promising methodology for the water control loops widely used in the water industry.

Description: To understand the current status of, and factors related to interpersonal sensitivity (IS) and loneliness among Chinese gay men. The Chinese version SCL-90-R was used to evaluate the status of IS, and the short-form UCLA Loneliness scale (ULS-8) was used for assessing loneliness level. Associations between demographics and IS were examined by chi-square tests and multivariable logistic regress analysis. Linear regression was used to assess the correlations between demographic factors and IS and loneliness. Dating practices and venues were summarized by multiple responses. Gay men who screened positive IS was identified in 36%. Age (OR25–29 = 8.731, 95% CI 2.296 to 33.139), education level (ORcollege = 0.037, 95% CI 0.046 to 0.911), being the only-child at home (ORyes = 4.733, 95% CI 2.293 to 9.733), monthly income (OR〉7000 = 0.228, 95% CI 0.055 to 0.944), numbers of current sexual partners (OR1 = 0.285, 95% CI 0.129 to 0.629; OR2 = 0.109 95% CI 0.027 to 0.431) were related to IS. IS was also associated with a higher score of ULS-8 (β = 6.903, p 〈 0.001). Other variables associated with the score of ULS-8 included: living in a non-nuclear family (β = 0.998, p = 0.020), being a college student (β = −1.556, p = 0.044), having a higher monthly income (β for 3000–5000 yuan = −1.177, p = 0.045; β for over 7000 yuan = −2.207, p = 0.002), having sexual partners (all β 〈 1, p 〈 0.001), being the only-child (β = 1.393, p = 0.005). Nearly half of the sample (46.78%) reported that they looked for dating partners on the Internet or dating apps. IS and loneliness are positively correlated. Our study suggests that more humanistic care and social support should be given to Chinese gay men.

Description: In recent years, entity-based ranking models have led to exciting breakthroughs in the research of information retrieval. Compared with traditional retrieval models, entity-based representation enables a better understanding of queries and documents. However, the existing entity-based models neglect the importance of entities in a document. This paper attempts to explore the effects of the importance of entities in a document. Specifically, the dataset analysis is conducted which verifies the correlation between the importance of entities in a document and document ranking. Then, this paper enhances two entity-based models—toy model and Explicit Semantic Ranking model (ESR)—by considering the importance of entities. In contrast to the existing models, the enhanced models assign the weights of entities according to their importance. Experimental results show that the enhanced toy model and ESR can outperform the two baselines by as much as 4.57% and 2.74% on NDCG@20 respectively, and further experiments reveal that the strength of the enhanced models is more evident on long queries and the queries where ESR fails, confirming the effectiveness of taking the importance of entities into account.

Description: Tissue-specific gene expression has long been recognized as a crucial key for understanding tissue development and function. Efforts have been made in the past decade to identify tissue-specific expression profiles, such as the Human Proteome Atlas and FANTOM5. However, these studies mainly focused on “qualitatively tissue-specific expressed genes” which are highly enriched in one or a group of tissues but paid less attention to “quantitatively tissue-specific expressed genes”, which are expressed in all or most tissues but with differential expression levels. In this study, we applied machine learning algorithms to build a computational method for identifying “quantitatively tissue-specific expressed genes” capable of distinguishing 25 human tissues from their expression patterns. Our results uncovered the expression of 432 genes as optimal features for tissue classification, which were obtained with a Matthews Correlation Coefficient (MCC) of more than 0.99 yielded by a support vector machine (SVM). This constructed model was superior to the SVM model using tissue enriched genes and yielded MCC of 0.985 on an independent test dataset, indicating its good generalization ability. These 432 genes were proven to be widely expressed in multiple tissues and a literature review of the top 23 genes found that most of them support their discriminating powers. As a complement to previous studies, our discovery of these quantitatively tissue-specific genes provides insights into the detailed understanding of tissue development and function.

Description: Sensor alignment plays a key role in the accurate estimation of the ballistic trajectory. A sparse regularization-based sensor alignment method coupled with the selection of a regularization parameter is proposed in this paper. The sparse regularization model is established by combining the traditional model of trajectory estimation with the sparse constraint of systematic errors. The trajectory and the systematic errors are estimated simultaneously by using the Newton algorithm. The regularization parameter in the model is crucial to the accuracy of trajectory estimation. Stein’s unbiased risk estimator (SURE) and general cross-validation (GCV) under the nonlinear measurement model are constructed for determining the suitable regularization parameter. The computation methods of SURE and GCV are also investigated. Simulation results show that both SURE and GCV can provide regularization parameter choices of high quality for minimizing the errors of trajectory estimation, and that our method can improve the accuracy of trajectory estimation over the traditional non-regularization method. The estimates of systematic errors are close to the true value.