An Empirical Model for Estimating Soil Thermal Diffusivity from Texture, Bulk Density, and Degree of Saturation

Soil thermal diffusivity κ is an essential parameter for studying surface and subsurface heat transfer and temperature changes. It is well understood that κ mainly varies with soil texture, water content θ, and bulk density ρb, but few models are available to accurately quantify the relationship. In this study, an empirical model is developed for estimating κ from soil particle size distribution, ρb, and degree of water saturation Sr. The model parameters are determined by fitting the proposed equations to heat-pulse κdata for eight soils covering wide ranges of texture, ρb, and Sr. Independent evaluations with published κdata show that the new model describes the κ(Sr) relationship accurately, with root-mean-square errors less than 0.75 × 10−7 m2 s−1. The proposed κ(Sr) model also describes the responses of κ to ρb changes accurately in both laboratory and field conditions. The new model is also used successfully for predicting near-surface soil temperature dynamics using the harmonic method. The results suggest that this model provides useful estimates of κ from Sr, ρb, and soil texture

Mining Weighted Frequent Closed Episodes over Multiple Sequences

Frequent episode discovery is introduced to mine useful and interesting temporal patterns from sequential data. The existing episode mining methods mainly focused on mining from a single long sequence consisting of events with time constraints. However, there can be multiple sequences of different importance as the persons or entities associated with each sequence can be of different importance. Aiming to mine episodes in multiple sequences of different importance, we first define a new kind of episodes, i.e., the weighted frequent closed episodes, to take sequence importance, episode distribution and occurrence frequency into account together. Secondly, to facilitate the mining of such new episodes, we present a new concept called maximal duration serial episodes to cut a whole sequence into multiple maximum episodes using duration constraints, and discuss its properties for episode shrinking processing. Finally, based on the theoretical properties, we propose a two-phase approach to efficiently mine these new episodes. In Phase I, we adopt a level-wise episode shrinking framework to discover the candidate frequent closed episodes with the same prefixes, and in Phase II, we match the candidates with different prefixes to find the frequent close episodes. Experiments on simulated and real datasets demonstrate that the proposed episode mining strategy has good mining effectiveness and efficiency

An Improved Thermo-TDR Technique for Monitoring Soil Thermal Properties, Water Content, Bulk Density, and Porosity

The thermo-time domain reflectometry (thermo-TDR) technique is valuable for monitoring in situ soil water content (θ), thermal properties, bulk density (ρb), porosity (n), and air-filled porosity (na) in the vadose zone. However, the previous thermo-TDR sensor has several weaknesses, including limited precision of TDR waveforms due to the short probe length, small measurement volume, and thermal property estimation errors resulting from finite probe properties not accounted for by the heat pulse method. We have developed a new thermo-TDR sensor design for monitoring θ, thermal properties, ρb, n, and na. The new sensor has a robust heater probe (outer diameter of 2.38 mm and length of 70 mm) and a 10-mm spacing between the heater and sensing probes, which provides a sensing volume three times larger than that of the previous sensor. The identical cylindrical perfect conductors and the tangent line–second-order bounded mean oscillation theories were applied to analyze the raw data. Laboratory tests showed that θ values determined with the new sensor had a RMSE of 0.014 m3 m−3 compared with 0.016 to 0.026 m3 m−3 with the previous sensor. Soil thermal property estimates with the new sensor agreed well with modeled values. Soil ρb, n, and na derived from θ and thermal properties were consistent with those derived from gravimetric measurements. Thus, the new thermo-TDR sensor provides more accurate θ, thermal properties, ρb, n, and na values than the previous sensor

Experimental Time-Optimal Universal Control of Spin Qubits in Solids

Quantum control of systems plays an important role in modern science and technology. The ultimate goal of quantum control is to achieve high-fidelity universal control in a time-optimal way. Although high-fidelity universal control has been reported in various quantum systems, experimental implementation of time-optimal universal control remains elusive. Here, we report the experimental realization of time-optimal universal control of spin qubits in diamond. By generalizing a recent method for solving quantum brachistochrone equations [X. Wang et al., Phys. Rev. Lett. 114, 170501 (2015)], we obtained accurate minimum-time protocols for multiple qubits with fixed qubit interactions and a constrained control field. Single- and two-qubit time-optimal gates are experimentally implemented with fidelities of 99% obtained via quantum process tomography. Our work provides a time-optimal route to achieve accurate quantum control and unlocks new capabilities for the emerging field of time-optimal control in general quantum systems.National Basic Research Program of China (973 Program) (Grants 2013CB921800 and 2016YFB0501603)National Natural Science Foundation (China) (Grants 11227901, 31470835, and 11275183)Chinese Academy of Sciences. Strategic Priority Research Program (Grant XDB01030400)National Science Foundation (U.S.) (Project CCF-1350397

Diversity patterns and conservation gaps of Magnoliaceae species in China

Postponed access: the file will be available after 2023-12-27Magnoliaceae, a primitive group of angiosperms and distinguished ornamental plants with more than 100 species in China, is one of the most threatened plant family in the wild due to logging, habitat loss, over-collection and climate change. To provide a scientific guide of its conservation for policymakers, we explore the diversity patterns of 114 Magnoliaceae species in China using three diversity indices (species richness, weighted endemism, β-diversity) with a spatial resolution of 10 km by 10 km. Two methods, the top 5% richness algorithm and complementary algorithm, are used to identify diversity hotspots. Conservation gaps are recognized by overlapping the diversity hotspots with Chinese nature reserves. Our results indicate that Magnoliaceae species richness and weighted endemism are high in tropical to subtropical low montane forests in southern China, exceptionally high in southernmost Yunnan and boundary of Guizhou, Guangxi and Hunan. The β-diversity are scattered in southern China, suggesting a different species composition among grid cells. We identify 2524 grids as diversity hotspots for Magnoliaceae species in China, with 24 grids covered by three diversity indices (first-level diversity hotspots), 561 grids covered by two indices (second-level diversity hotspots) simultaneously and 1939 grids (76.8%) covered by only one index (third-level diversity hotspots). The first-level diversity hotspots include over 70% of the critically endangered Magnoliaceae species and are the priority areas for Magnoliaceae conservation. However, only 24% of the diversity hotspots fall in nature reserves and only ten grids are from the first-level diversity hotspots. Zhejiang, Guizhou and Fujian have less than 20% of diversity hotspots covered by nature reserves and need attention in future Magnoliaceae conservation. Using multiple diversity indices and algorithms, our study identifies diversity hotspots and conservation gaps and provides scientific basis for Magnoliaceae conservation in future.acceptedVersio

Protective Effect of Freeze-Dried Fruit Powder of Phyllanthus emblica L. on Acute and Chronic Hyperuricemia and Liver and Kidney Injuries in Mice

Objective: To explore the protective effect of the freeze-dried fruit powder of Phyllanthus emblica L. (PEFP) against acute and chronic hyperuricemia (HUA) and liver and kidney injuries in mice. Methods: Mouse models of acute and chronic HUA were established by intraperitoneal injection of hypoxanthine and potassium oxazinate, respectively. Meanwhile, PEFP at 75, 150 and 300 mg/kg mb were orally given to the mice in the intervention group for seven days. The levels of uric acid (UA), creatinine (CRE), blood urea nitrogen (BUN), aspartate aminotransferase (AST) and alanine aminotransferase (ALT) in the serum, and the activities of xanthine oxidase (XOD) and adenosine deaminase (ADA) in the serum and liver were detected. Liver and kidney indexes were calculated, and the pathological characteristics of liver and kidney tissues were observed by hematoxylin and eosin (HE) staining. Results: Compared with the model group, PEFP at 150 and 300 mg/kg mb significantly reduced the liver and kidney indexes (P < 0.01) and lowered serum UA, BUN, CRE, and AST levels in mice with acute hyperuricemia (P < 0.05 or P < 0.01). PEFP at 75, 150 and 300 mg/kg mb significantly inhibited serum and liver XOD and ADA activities (P < 0.01), and PEFP at 300 mg/kg mb lowered serum ALT levels in mice with acute hyperuricemia (P < 0.01). Meanwhile, all three doses of PEFP significantly reduced the liver and kidney indexes (P < 0.01), lowered serum UA, BUN and ALT levels (P < 0.01), and inhibited serum and liver XOD activities and serum ADA activity in mice with chronic hyperuricemia (P < 0.01). PEFP at 150 and 300 mg/kg mb lowered serum CRE and AST levels and liver ADA activity (P < 0.01). PEFP ameliorated the pathological changes of the liver and kidney in mice with acute and chronic hyperuricemia. Conclusion: PEPP can effectively decrease serum UA levels in mice with acute and chronic hyperuricemia, which may be related to the inhibition of XOD and ADA activities in the serum and liver, and the promotion of renal uric acid excretion, and can also exert renal and hepatoprotective effects