ALBERT

Description: Dynamic stall control of a S809 airfoil is numerically investigated by implementing a co-flow jet (CFJ). The numerical methods of the solver are validated by comparing results with the baseline experiment as well as a NACA 6415-based CFJ experiment, showing good agreement in both static and dynamic characteristics. The CFJ airfoil with inactive jet is simulated to study the impact that the jet channel imposes upon the dynamic characteristics. It is shown that the presence of a long jet channel could cause a negative effect of decreasing lift and increasing drag, leading to fluctuating extreme loads in terms of drag and moment. The main focus of the present research is the investigation of the dynamic characteristics of the CFJ airfoil with three different jet momentum coefficients, which are compared with the baseline, giving encouraging results. Dynamic stall can be greatly suppressed, showing a very good control performance of significantly increased lift and reduced drag and moment. Analysis of the amplitude of variation in the aerodynamic coefficients indicates that the fluctuating extreme aerodynamic loads are significantly alleviated, which is conducive to structural reliability and improved life cycle. The energy consumption analysis shows that the CFJ concept is applicable and economical in controlling dynamic stall.

Description: Natural disasters may be of significant impact on overhead transmission lines and cause communication outage related to pilot protection. This paper aims at reconstructing communication channels and maintaining functions of pilot-wire differential protections after the main channel fails. With the development of smart grids as well as new communication technologies, wireless sensor networks (WSNs) have been potential means for realizing reconstructed communication channels (RCCs) without further installation. For a reliable design, system arrangement and the communication structure were presented. Theoretical planning of sensor nodes was formulated, which enjoys advantages such as high reliability, cost optimization, and capacity of satisfying the connectivity of the communication network. To meet the need of time delay, a novel routing protocol for WSNs was proposed with three stages including route establishment, route discovery and route maintenance, which ensured the directional propagation of data packets. Practical experiments and simulation results indicate that the proposed RCC scheme can satisfy time delay of protection relaying in emergency communication channel, as well as guarantee the connectivity of networks when some WSN nodes are damaged.

Description: Water, Vol. 9, Pages 617: Recent Sedimentation Rates of Shallow Lakes in the Middle and Lower Reaches of the Yangtze River: Patterns, Controlling Factors and Implications for Lake Management Water doi: 10.3390/w9080617 Authors: Min Xu Xuhui Dong Xiangdong Yang Xu Chen Qinghui Zhang Qian Liu Rong Wang Min Yao Thomas Davidson Erik Jeppesen Significantly increased sedimentation rates (SRs) in lakes worldwide in recent decades due to higher inputs of silt and eutrophication have led to significant environmental problems such as lake size diminishment and degraded water quality. Many lakes in the middle and lower reaches of the Yangtze River basin (MLYB) have followed this pattern. For effective lake management, it is essential to understand the pattern and drivers of SRs in these lakes. Fourteen typical lakes in the MLYB were chosen to examine the spatiotemporal patterns of SRs and identify the drivers over different time periods. Since 1900, SRs increased from <0.2 to 0.3–0.6 g·cm−2·year−1, particularly notable during 1930–1990. Combined with climatic factors, SR correlated negatively with lake (catchment) size and abundance of aquatic vegetation, whereas other lake features including nutrient status did not contribute significantly to the variation in SRs, due to the fast decomposition processes of organic matter in shallow lakes. Detrimental land use practices especially reclamation for croplands and rapid urbanization was revealed to elevate SRs pronouncedly. We propose various management strategies aiming to maintain SR reference condition at ~0.16 ± 0.08 g·cm−2·year−1, which is analogous to the SR value between 1850 and 1900.

Description: We fabricated a 3D sandwich hybrid material composed of graphene and vertically aligned carbon nanotube forests (VACNTs) using chemical vapor deposition. The graphene was first synthesized on Cu foil. Then it was transferred to a substrate which had a pre-deposited catalyst Fe film and a buffer film of Al2O3 for the growth of VACNTs. The VACNTs were grown underneath the graphene and lifted up the graphene. The graphene, with its edges anchored on the Al2O3, provided a constrained boundary condition for the VACNTs and hence affected the growth height and mechanical strength of the VACNTs. We prepared three groups of samples: VACNTs without graphene, VACNTs with graphene transferred once (1-Gr/VACNTs), and VACNTs with graphene transferred twice (2-Gr/VACNTs). A nano-indentation system was used to measure the reduced compressive modulus (Er) and hardness (H). The Er and H of Gr/VACNTs increased with the number of transfers of the anchored graphene. The 2-Gr/VACNTs had the largest Er and H, 23.8 MPa and 912 KPa, which are 6.6 times and 5.2 times those of VACNTs without the anchored graphene, respectively. In this work, we have demonstrated a simple method to increase the mechanical properties and suppress the height of VACNTs with the anchored graphene and number of transfers.

Description: Remote Sensing, Vol. 10, Pages 1113: GPS/BDS Medium/Long-Range RTK Constrained with Tropospheric Delay Parameters from NWP Model Remote Sensing doi: 10.3390/rs10071113 Authors: Ying Xu Chen Wu Lei Li Lizi Yan Min Liu Shengli Wang Tropospheric delay is a major error source that affects the performance of the Global Navigation Satellite Systems (GNSS) Real Time Kinematic (RTK) positioning especially for the medium/long-range baseline. Although high precision tropospheric delay can be estimated by GNSS carrier phase measurement, together with position and ambiguity, a relatively long period of convergence time is necessary. In this study, we develop a new GPS/BDS RTK algorithm constrained with a tropospheric delay parameters from Numerical weather prediction (NWP) model for medium/long-range baselines. The accuracy of the tropospheric delays derived from NWP is assessed through comparisons with the results of GAMIT (GNSS at MIT). The positioning performance with standard GPS RTK, standard GPS/BDS RTK, the developed NWP-constrained GPS RTK and NWP-constrained GPS/BDS RTK over medium/long-range baselines are compared in terms of the initialization time and the positioning accuracy. Experiment results show that the mean differences between the NWP and GAMIT zenith tropospheric delay (ZTD) are between −5.50 mm and 5.60 mm, and the RMS values of the NWP ZTD residuals are from 24.02 mm to 32.62 mm. A reduction in the initialization time of over 41% and 58% for medium- and long-range baselines can be achieved with the NWP-constrained RTK (both GPS alone and GPS/BDS RTK solutions) compared to the standard RTK solution, respectively. An improvement of over 30% can be found with the GPS/BDS RTK compared with that of the GPS alone RTK for both standard and the NWP-constrained modes. The positioning precision of NWP-constrained GPS/BDS RTK is better than 3 cm in the horizontal direction and better than 5 cm in the vertical direction, which satisfies the requirement of the precise positioning service.

Description: The mixed cationic collector cetyltrimethylammonium chloride (CTAC) and nonionic collector octanol (OCT) was found to exhibit a synergistic effect on the flotation and adsorption of muscovite. To understand the underlying synergistic mechanism, flotation, contact angle, surface tension, and adsorption measurements were carried out. The results obtained from flotation measurements indicated that the mixed CTAC/OCT exhibits a better collecting ability than CTAC or OCT. The recovery of muscovite with CTAC only rapidly decreased from 97.25% at pH 2.64 to 75.26% at pH 5.82, followed by a flat horizontal at a pH is higher than 6. In contrast, a high recovery of greater than 85% muscovite was observed using mixed CTAC/OCT at α CTAC = 0.67 (the mole ratio of CTAC:OCT = 2:1) over the investigated pH range. From the surface activity parameters (CMC, γ CMC, Γmax, Amin) estimated from surface measurements and interaction parameters (βm, βσ), in addition to the micellar and interfacial compositions ( x 1 m , x 1 σ ) obtained from the theory of regular solutions, a synergistic effect is evident in the mixed micelle and at the water/air interface. Moreover, the mixed CTAC/OCT at α CTAC = 0.67 exhibited the maximum synergistic interaction. The results obtained from surface tension measurements indicated that the mixed CTAC/OCT exhibits considerably higher surface activities compared to single CTAC or OCT. The contact angle results confirmed that the mixed CTAC/OCT is a better collector than the individual CTAC or OCT for the flotation of muscovite. According to the results obtained from adsorption experiments, compared with that of individual CTAC or OCT, the amounts of CTAC and OCT adsorbed on the muscovite surface are considerably increase in the mixed systems because of co-adsorption. Based on these results, the mixed CTAC/OCT exhibits a remarkable synergistic effect during the flotation and adsorption of muscovite.

Description: Algorithms, Vol. 11, Pages 137: Learning Heterogeneous Knowledge Base Embeddings for Explainable Recommendation Algorithms doi: 10.3390/a11090137 Authors: Qingyao Ai Vahid Azizi Xu Chen Yongfeng Zhang Providing model-generated explanations in recommender systems is important to user experience. State-of-the-art recommendation algorithms—especially the collaborative filtering (CF)- based approaches with shallow or deep models—usually work with various unstructured information sources for recommendation, such as textual reviews, visual images, and various implicit or explicit feedbacks. Though structured knowledge bases were considered in content-based approaches, they have been largely ignored recently due to the availability of vast amounts of data and the learning power of many complex models. However, structured knowledge bases exhibit unique advantages in personalized recommendation systems. When the explicit knowledge about users and items is considered for recommendation, the system could provide highly customized recommendations based on users’ historical behaviors and the knowledge is helpful for providing informed explanations regarding the recommended items. A great challenge for using knowledge bases for recommendation is how to integrate large-scale structured and unstructured data, while taking advantage of collaborative filtering for highly accurate performance. Recent achievements in knowledge-base embedding (KBE) sheds light on this problem, which makes it possible to learn user and item representations while preserving the structure of their relationship with external knowledge for explanation. In this work, we propose to explain knowledge-base embeddings for explainable recommendation. Specifically, we propose a knowledge-base representation learning framework to embed heterogeneous entities for recommendation, and based on the embedded knowledge base, a soft matching algorithm is proposed to generate personalized explanations for the recommended items. Experimental results on real-world e-commerce datasets verified the superior recommendation performance and the explainability power of our approach compared with state-of-the-art baselines.

Description: Accurate forecasting of annual runoff is necessary for water resources management. However, a runoff series consists of complex nonlinear and non-stationary characteristics, which makes forecasting difficult. To contribute towards improved prediction accuracy, a novel hybrid model based on the empirical mode decomposition (EMD) for annual runoff forecasting is proposed and applied in this paper. Firstly, the original annual runoff series is decomposed into a limited number of intrinsic mode functions (IMFs) and one trend term based on the EMD, which makes the series stationary. Secondly, it will be forecasted by a least squares support vector machine (LSSVM) when the IMF component possesses chaotic characteristics, and simulated by a polynomial method when it does not. In addition, the reserved trend term is predicted by a Gray Model. Finally, the ensemble forecast for the original runoff series is formulated by combining the prediction results of the modeled IMFs and the trend term. Qualified rate (QR), root mean square errors (RMSE), mean absolute relative errors (MARE), and mean absolute errors (MAE) are used as the comparison criteria. The results reveal that the EMD-based chaotic LSSVM (EMD-CLSSVM) hybrid model is a superior alternative to the CLSSVM hybrid model for forecasting annual runoff at Shangjingyou station, reducing the RMSE, MARE, and MAE by 39%, 28.6%, and 25.6%, respectively. To further illustrate the stability and representativeness of the EMD-CLSSVM hybrid model, runoff data at three additional sites, Zhaishang, Fenhe reservoir, and Lancun stations, were applied to verify the model. The results show that the EMD-CLSSVM hybrid model proved its applicability with high prediction precision. This approach may be used in similar hydrological conditions.

Description: Compared with the extensively surveyed temperate and boreal peatlands, subtropical peatlands have received rather little scientific attention. In this study, spatial variations in water chemistry were investigated in 57 samples collected from three subtropical peatlands (central China). Generally, water pH and major cation concentrations of these samples approached the characteristics of poor fens along the bog–rich fen gradient. Four distinct groups were identified by cluster analysis and principal component analysis. High concentrations of trace elements in Group I were probably linked to airborne dust pollutants from a nearby road under construction. Low pH values and low major cation concentrations in Group II may be attributed to the great cation exchange capacity of Sphagnum. In contrast, samples in Group III, mainly collected from sites suffering from Sphagnum harvest, showed high pH levels and major cation concentrations. Relatively low concentrations of trace elements (except boron) in Group IV can be regarded as reference conditions for restoration efforts in these peatlands. Taken together, spatial variations in the water chemistry of the three peatlands were closely linked to natural processes (e.g., cation exchange of Sphagnum) and anthropogenic pressures (e.g., Sphagnum harvest). Overall, the mean health risk values of the six trace elements were low, indicating good water quality in these peatlands. This study provided baseline water chemistry information for the sustainable management of these subtropical peatlands, as well as other similar ecosystems.