Integration of Special Sensor Microwave/Imager (SSM/I) and in Situ Data for Snow Studies from Space

The Special Sensor Microwave/Imager (SSM/I) radiometer is a useful tool for monitoring snow conditions and estimating snow water equivalent and wetness because it is sensitive to the changes in the physical and dielectric properties of snow. Development and improvement of SSM/I snow-related algorithms is hampered generally by the lack of quantitative snow wetness data and the restriction of a fixed uniform footprint. Currently, there is a need for snow classification algorithms for terrain where forests overlie snow cover. A field experiment was conducted to examine the relationship between snow wetness and meteorological variables. Based on the relationship, snow wetness was estimated concurrently with SSM/I local crossing time at selected footprints to develop an SSM/I snow wetness algorithm. For the improvement of existing algorithms, SSM/I observations were linked with concurrent ground-based snow data over a study area containing both sparse- and medium-vegetated regions. Unsupervised cluster analysis was applied to separate SSM/I brightness temperature (Tb) data into groups. Six typical SSM/I Tb signatures, based on cluster means of desired snow classes, were identified. An artificial neural network (ANN) classifier was designed to learn the typical Tb patterns Ill for land-surface snow cover classification. An ANN approximator was trained with the relations between inputs of SSM/I Tb observations and outputs of ground-based snow water equivalent and wetness. Results indicated that snow wetness estimated from concurrent air temperature could provide the ground-based data needed for the development of SSM/I algorithms. The use of cluster means might be sufficient in ANN supervised learning for snow classification, and the ANN has the potential to be trained for retrieving different snow parameters simultaneously from SSM/I data. It is concluded that the ANN approach may overcome the drawbacks and limitations of the existing SSM/I algorithms for land-surface snow classification and parameter estimation over varied terrain. This study demonstrated a nonlinear retrieval method towards making the inferences of snow conditions and parameters from SSM/I data over varied terrain operational

Causality-Based Feature Importance Quantifying Methods: PN-FI, PS-FI and PNS-FI

In the current ML field models are getting larger and more complex, and data used for model training are also getting larger in quantity and higher in dimensions. Therefore, in order to train better models, and save training time and computational resources, a good Feature Selection (FS) method in the preprocessing stage is necessary. Feature importance (FI) is of great importance since it is the basis of feature selection. Therefore, this paper creatively introduces the calculation of PN (the probability of Necessity), PN (the probability of Sufficiency), and PNS (the probability of Necessity and Sufficiency) of Causality into quantifying feature importance and creates 3 new FI measuring methods, PN-FI, which means how much importance a feature has in image recognition tasks, PS-FI that means how much importance a feature has in image generating tasks, and PNS-FI which measures both. The main body of this paper is three RCTs, with whose results we show how PS-FI, PN-FI, and PNS-FI of 3 features, dog nose, dog eyes, and dog mouth are calculated. The experiments show that firstly, FI values are intervals with tight upper and lower bounds. Secondly, the feature dog eyes has the most importance while the other two have almost the same. Thirdly, the bounds of PNS and PN are tighter than the bounds of PS.Comment: 7 page

Loss of soil carbon and nitrogen indicates climate change-induced alterations in a temperate forest ecosystem

Climate warming is expected to influence terrestrial biogeochemical cycles by modifying the quality and quantity of plant litter input to soils. Although a growing number of studies recognize the importance of plant litter input in influencing the loss of soil organic matter (SOM) through a phenomenon called the priming effect (PE), the exact mechanisms behind PE are not well known. Importantly, most PE research is based on short term pot experiments in which fresh organic matter (FOM) input is represented by a single addition of compounds of unnaturally simple chemical composition. Furthermore, only a few studies exist in which the PE was explored in terms of organic C (SOC) and total N content in the soil. Here, we report results of a 3-year long litter manip-ulation study conducted under natural conditions in a broadleaved Korean pine forest in N-E China. We show that the extra supply (twice the normal input) of aboveground tree litter composing of conifer needles, leaves and small twigs was associated not only with slightly decreased SOC (by 5%) but especially that of soil total N (STN) (by 15%) content in the top soil (0-5 cm depth). In contrast, removal of litter resulted in an increased (ca. 15%) amount of both SOC and STN during the study when compared to control soils receiving natural litter input. Despite the enhanced leaf litter decomposition rate in the treatment receiving extra litter, the changes in SOC and STN were related neither to soil microbial biomass nor to community composition. The amount of N lost (40.0 g m- 2) in the soil due to litter addition was ca. three times the amount of N added (12.3 g m- 2) via the litter, while the amount of C lost (238 g m- 2) was about one third of that added (940 g m- 2), suggesting that soil N in our research site is more prone to the PE than soil C. As we did not manipulate belowground FOM input, our results suggest that input of aboveground litter rather than that by roots explained the PE in our study. Results of our long-term study conducted under natural conditions in undisturbed forest soils highlight the large potential of recalcitrant, aboveground litter to affect the PE, which should not go unnoticed when predicting the role of forest soils under conditions (such as climate warming) when these soils act as C sinks.Peer reviewe

Evaluating the value of synchrotron radiation phase-contrast CT imaging in the study of knee joint microstructure

The knee joint is one of the tissues that often appear diseased, and the pathogenesis owing to its structure. Therefore, the micro-structure of the knee joint was studied by synchrotron radiation phasecontrast CT imaging (SRPCI-CT). The contrast and the sharpness of the reconstructed slice were calculated and analysed. From these results, the layer structure of the joint tissue can be seen. The cartilage layer (including the meniscus) is about 1.44 mm, and the epiphyseal layer is about 2.25 mm, which conforms to the actual situation of rat knees. From the 3D images, the structure of the meniscus and the epiphyseal bone can be observed. The epiphyseal bone line is also particularly obvious. Simultaneously, the epiphyseal bone also has a mesh structure, which has the characteristics of both cartilage and tibia. Further research on the tibia can determine that the trabecular bone line is about 130 microns. Finally, the bone volume fraction (BVF) of the joint, the data also reflect the existence of a layer structure, and its scale distribution is consistent with the results of sharpness and contrast analysis. The SRPCI-CT can play an important role in the study micro-structure of joints

FREQUENCY AND LENGTH ADJUSTMENT OF A DUMBBELL FOR THE PEFP LOW-BETA SRF CAVITY*

Abstract This paper describes a method to adjust the frequency and the length of a dumbbell used to fabricate the PEFP low-beta superconducting RF cavity. A tuning program is used to calculate the π mode frequency of each half-cell according to the resonant frequency of a TM010 passband and the perturbation frequency shifts of a dumbbell. According to the frequency difference between the two half cells and the frequency sensitivity coefficients, we can determine the tuning length in the axial direction or the trimming length at the equator to make the two half cells have the same frequency and length. In order to measure the frequency and to compensate for the length of a PEFP dumbbell for a stiffening-ring welding shrinkage, a frequency measurement set and length tuning set have been fabricated

The progress of IPS therapy on the heart and neural disease

Heart and brain (AD) diseases are easier to happen to people who are aged. Traditional therapies are not able to cure the disease and the stem cell is chosen to be applied as new therapy. However, there are many moral problems related to stem cells, so another typical therapy is developed, which is IPS therapy. IPS therapy is mainly about inducing stem cells from the somatic cells of patients then deriving them into typical cells we need to treat diseases, which avoid many moral problems. In this article, IPS therapy on treating heart disease on different species and its application on AD are summarized. Though there are disadvantages of IPS therapy, IPS therapy is promising based on the current progress

Co-seismic Earth’s rotation change caused by the 2012 Sumatra earthquake

Earthquakes heavily deform the crust in the vicinity of the fault, which leads to mass redistribution in the earth interior. Then it will produce the change of the Earth’s rotation (polar motion and length of day) due to the change of Earth inertial moment. This paper adopts the elastic dislocation to compute the co-seismic polar motion and variation in length of day (LOD) caused by the 2011 Sumatra earthquake. The Earth’s rotational axis shifted about 1 mas and this earthquake decreased the length of day of 1 μs, indicating the tendency of earthquakes make the Earth rounder and to pull the mass toward the centre of the Earth. The result of variation in length of day is one order of magnitude smaller than the observed results that are available. We also compared the results of three fault models and find the co-seismic change is depended on the fault model

Effects of Huge Earthquakes on Earth Rotation and the length of Day

We calculated the co-seismic Earth rotation changes for several typical great earthquakes since 1960 based on Dahlen¡¦s analytical expression of Earth inertia moment change, the excitation functions of polar motion and, variation in the length of a day (ΔLOD). Then, we derived a mathematical relation between polar motion and earthquake parameters, to prove that the amplitude of polar motion is independent of longitude. Because the analytical expression of Dahlen¡¦s theory is useful to theoretically estimate rotation changes by earthquakes having different seismic parameters, we show results for polar motion and ΔLOD for various types of earthquakes in a comprehensive manner. The modeled results show that the seismic effect on the Earth¡¦s rotation decreases gradually with increased latitude if other parameters are unchanged. The Earth¡¦s rotational change is symmetrical for a 45° dip angle and the maximum changes appear at the equator and poles. Earthquakes at a medium dip angle and low latitudes produce large rotation changes. As an example, we calculate the polar motion and ΔLOD caused by the 2011 Tohoku-Oki Earthquake using two different fault models. Results show that a fine slip fault model is useful to compute co-seismic Earth rotation change. The obtained results indicate Dahlen¡¦s method gives good approximations for computation of co-seismic rotation changes, but there are some differences if one considers detailed fault slip distributions. Finally we analyze and discuss the co-seismic Earth rotation change signal using GRACE data, showing that such a signal is hard to be detected at present, but it might be detected under some conditions. Numerical results of this study will serve as a good indicator to check if satellite observations such as GRACE can detect a seismic rotation change when a great earthquake occur