ALBERT

Description: Due to its low water solubility and slow dissolution rate, genipin was micronized by an antisolvent precipitation process using ethanol as solvent and n -hexane as antisolvent. The effects of various experimental parameters on the mean particle size (MPS) of micronized genipin were investigated. By analysis of variance, only the concentration of the genipin solution has a significant effect on the MPS in genipin micronization. Under the optimum conditions, micronized genipin with an MPS of 1.8 μm was obtained. The micronized genipin was characterized by various methods, e.g., scanning electron microscopy and thermogravimetry. The analysis results indicated that the chemical structure of micronized genipin was not changed, but the crystallinity was reduced. The dissolution rate and solubility of the micronized genipin were 2.08 and 1.64 times that of the raw drug. In addition, the residual amounts of n -hexane and ethanol were less than the International Conference on Harmonization limit for solvents. Micronized genipin with a mean particle size of 1.8 μm was prepared by the antisolvent precipitation process. The chemical structure of micronized genipin remained unchanged, but the crystallinity was reduced. The dissolution rate and solubility of the micronized genipin were 2.08 and 1.64 times that of the raw drug, and the amounts of residual n -hexane and ethanol were lower than the International Conference on Harmonization limit for solvents.

Description: A novel chemical soft-sensor approach for the prediction of the melt index (MI) in the propylene polymerization industry is presented. The MI is considered as one of the important variables of quality that determine the product specifications. Thus, a reliable estimation of the MI is crucial in quality control. An accurate optimal predictive model of MI values with the relevance vector machine (RVM) is proposed, where the RVM is employed to build the MI prediction model; a modified particle swarm optimization (MPSO) algorithm is then introduced to optimize the parameter of the RVM, and the MPSO-RVM model is thereby developed. An online correcting strategy (OCS) is further carried out to update the modeling data and to revise the model's parameter self-adaptively whenever model mismatch happens. Based on the data from a real polypropylene production plant, a detailed comparison is carried out among the least squares support vector machine (LS-SVM), RVM, MPSO-RVM, and OCS-MPSO-RVM models. The research results reveal the prediction accuracy and validity of the proposed approach. A chemical soft-sensor approach for the prediction of the melt index (MI) in the propylene polymeriza-tion industry is presented. The relevance vector machine (RVM) is employed to build the MI prediction model. A modified particle swarm optimization algorithm is then introduced to optimize the parameter of the RVM and an online correcting strategy is carried out to update the modeling data.

Description: Using the PPMLR-MHD global simulation model, we examined the Kelvin-Helmholtz (K-H) instability at the low-latitude boundary layer (LLBL) under northward interplanetary magnetic field (IMF) conditions with various solar wind speeds (400, 600, and 800 km/s). The spatial distribution of the K-H wave power in the equatorial plane shows two distinct power populations, referring to the two modes of K-H surface waves. The spatial evolution of K-H instability at the boundary layer is classified into four phases: quasi-stable, exponential growth, linear growth, and nonlinear phases. The boundary layer is quasi-stable near the subsolar point region. The K-H instability starts at about 30° longitude, and grows exponentially with a spatial growth rate of 0.28∼0.87 RE−1 until ∼45° longitude where the vortices fully develop. At larger longitudes, the instability grows linearly, while the vortices grow in size. From ∼80° longitude to the distant magnetotail, the K-H instability develops nonlinearly and the vortices roll up. The wave frequency, wavelength, and phase speed are given at various spatial points. Model results show that the higher solar wind speed generates K-H waves with higher frequency under the northward IMF, and the wavelengths and the phase speeds increase with the increase of the longitude. Moreover, we made a comparison of the K-H wave periods on Earth's, Mercury's and Saturn's magnetopauses by a proposed prediction method.

Description: Slow shock formation and structure associated with magnetic reconnection are investigated in the presence of sub-Alfvénic shear flow using a compressible resistive MHD model. It is found for the first time that one or two pairs of the slow shocks are formed in the inflow region away from the reconnection separatrices within compressible resistive MHD. The distributions of the slow shocks depend largely on the plasma beta and the shear flow velocity that lead to the increase of magnetic reconnection rate. One pair of the slow shocks is formed for β = 0.2 and two pairs of the slow shocks are generated for β = 1.0 with the shear flow velocity in the range 0.6 VA to 0.9 VA. For high plasma beta (β = 5.0), there is no slow shock formed outside the reconnection separatrices. The results can be applied to interpret slow shock observations at the dayside magnetopause.

Description: Abstract Whistler mode waves, particularly rising tone emissions, are important for nonlinear interactions with energetic electrons in the Earth's magnetosphere. In this letter, we evaluate the characteristics of rising tone whistler mode waves in three distinct regions: 1. inside the plasmasphere; 2. plasmapheric plumes, and 3. plasmatrough (outside the plasmapause). Our statistical results indicate that the occurrence rate of rising tone emissions tends to increase with increasing geomagnetic activity and is highest in plasmaspheric plumes among these three regions. Inside the plasmasphere, rising tone emissions typically occur in the outer portion of the plasmasphere, particularly near the dawnside. Moreover, the rising tone emissions inside the plasmasphere and plumes tend to be more field aligned than those in the plasmatrough. Our new findings of global wave properties of rising tone emissions are critical for understanding the generation of rising tone emissions and their effects on radiation belt electron dynamics.

Description: Abstract Seismic spectral ratios between the 3 September 2017 North Korean nuclear test (NKT2017) and four earlier Korean tests (25 May 2009, NKT2009; 12 February 2013, NKT2013; 6 January 20016, NKT2016J; and 9 September 2016, NKT2016S) are investigated. All the observed teleseismic P wave spectral ratios exhibit a unique notch at approximately 2.5 Hz, but it is not observed for spectral ratios of regional P and Lg waves. Meanwhile, for a given event pair, the network‐averaged Lg wave spectral ratio is similar to that of regional P wave, but with the explosions' source corner frequencies significantly reduced, supporting the conjecture by Fisk (2006, https://doi.org/10.1785/0120060023). We demonstrated that the observed notch of teleseismic P wave spectral ratios may be well modeled with interference between pP and P waves with an apparent pP‐P time delay ΔtpP of about 0.4 s for NKT2017, while regional P wave spectral ratios may be well fitted with source spectral ratios predicted by classical explosion source models including Mueller and Murphy (1971, https://doi.org/10.2172/4107998) (MM71), Denny and Johnson (1991, https://doi.org/10.1029/gm065p0001) (DJ91), and their two hybrids. Via the above modeling, yield sizes of the explosions and the depth of burials of NKT2009–2016S are determined as functions of NKT2017's buried depth h0. Our result indicate that, for h0 in the range of 600–1,100 m, the MM71‐related models give yield estimations about 100–300 kt for NKT2017, 3–7 kt for NKT2009, 6–15 kt for NKT2013 and NKT2016J, and 10–25 kt for NKT2016S, while yield sizes obtained by model DJ91 are much smaller. Nevertheless, for all the above source models, the obtained depths of burial estimations of NKT2009–2016S are always significantly smaller than NKT2017's depth of burial h0.

Description: The dielectric and ferroelectric characteristics of ( Sr x Ba 1− x ) Nb 2 O 6 unfilled tungsten bronze ceramics have been investigated together with the structure. The dielectric and ferroelectric characteristics of the present ceramics vary significantly with x , and the A1/A2-sites occupancy has been determined as the primary parameter governing this variation tendency. Ba ions tend to occupy A2-sites, Sr ions tend to occupy A1-sites, and one A1-site is empty. When the ratio of Sr / Ba is close to 1:4 (where four A2-sites are just occupied by Ba ions, and one A1-site is occupied by Sr ion while another A1-site is empty), the normal ferroelectric transition is observed with one anomaly in the tanδ– T curve ( x  = 0.25). When the ratio of Sr / Ba is far away from 1:4, the typical relaxor behavior is indicated together with three anomalies in the tanδ– T curve ( x  = 0.75). The incommensurate oxygen octahedral tilting and A-site random distribution are considered to be the structure origins for the relaxor ferroelectricity and low temperature dielectric relaxations.

Description: A novel chemical soft-sensor approach for the prediction of the melt index (MI) in the propylene polymerization industry is presented. The MI is considered as one of the important variables of quality that determine the product specifications. Thus, a reliable estimation of the MI is crucial in quality control. An accurate optimal predictive model of MI values with the relevance vector machine (RVM) is proposed, where the RVM is employed to build the MI prediction model; a modified particle swarm optimization (MPSO) algorithm is then introduced to optimize the parameter of the RVM, and the MPSO-RVM model is thereby developed. An online correcting strategy (OCS) is further carried out to update the modeling data and to revise the model's parameter self-adaptively whenever model mismatch happens. Based on the data from a real polypropylene production plant, a detailed comparison is carried out among the least squares support vector machine (LS-SVM), RVM, MPSO-RVM, and OCS-MPSO-RVM models. The research results reveal the prediction accuracy and validity of the proposed approach. A chemical soft-sensor approach for the prediction of the melt index (MI) in the propylene polymeriza-tion industry is presented. The relevance vector machine (RVM) is employed to build the MI prediction model. A modified particle swarm optimization algorithm is then introduced to optimize the parameter of the RVM and an online correcting strategy is carried out to update the modeling data.

Description: Polyelectrolyte-enhanced ultrafiltration was investigated for rhenium(VII) recovery from aqueous solutions by using polyquaternium-6 (PQ6) as a complexing agent. The effects of the operating parameters on the permeate flux ( J ) and the rhenium rejection coefficient ( R ) were studied. In the process of concentration, J declines slowly and R is about 1. The concentrated solution was used for the decomplexation. It takes 10 min to achieve the decomplexation equilibrium at a chloride ion concentration of 100 mg L –1 . The decomplexation percentage reaches 45.6 %. In the diafiltration process, rhenium is extracted effectively, and the purification of the regenerated PQ6 is satisfactory. The regenerated PQ6 was used to bind rhenium(VII). The binding capacity of the regenerated PQ6 is close to that of fresh PQ6. Polyelectrolyte-enhanced ultrafiltration was originally used to achieve the recovery of rhenium from aqueous solutions with the help of polyquaternium-6. The effects of various operating parameters on the permeate flux and the rhenium rejection coefficient were investigated. The integration of four experiments including concentration, decomplexation, diafiltration and reuse of the regenerated polymer was carried out.

Description: Striking networks of livestock tracks, or terracettes, molded to the contours are a common feature on hilly rangelands of the semiarid Loess Plateau, one of the regions with the most severe soil erosion in the world. The formation of livestock tracks results in modified micro-topography and ecological processes and leads to strong patterns in spatial distribution of vegetation, water, and nutrients. We investigated the spatial pattern of the topo-edaphic, hydrological, biogeochemical, and biological attributes of these terracette landscapes and explored their potential implications to ecosystem functions. The results showed strong spatial heterogeneity in topo-edaphic and biological structure of these landscapes, organized with three segments of a basic landscape unit—track, shoulder, and interslope. The above- and below-ground biomass and soil nutrients concentrated in the shoulder segment forming a “band of fertility”. The network of livestock tracks likely reduced surface runoff and erosion by intercepting runoff and facilitate infiltration, while posing little risk of increasing shallow slope failures given the structure of loess soil. There appears a positive feedback loop for maintaining the structure of terracette landscapes. Trampling by goats maintains the tracks, which leads to spatial heterogeneity in biophysical structure and processes. The network of tracks enabled the goats to travel and graze in ways that reduce energy expenditure and increase foraging efficiency, which leads to strongly preferential use of the tracks by the goats. There are also evidence of a possible process resemble a slope parallel retreat at a micro-scale, which may result in upslope movement of the terracettes. There may be important functional differences between landscapes with and without networks of livestock tracks, in regulating water runoff and soil erosion, forage production, and soil carbon storage. These functional differences may have significant implications to land use policies and practices aiming at soil and water conservation and socioecological sustainability of the Loess Plateau.