Study on Desiccation and Collection Models for Banana Stems

In this study, 8 kinds of desiccation models and 3 kinds of collection models were studied for banana stems. The results showed that the crushing-com- pression-air drying processing model showed the best desiccation effect for banana stems. Under this desiccation model, the moisture content was reduced from 90.5% to 19.93% with weight reduced by 75.2%; after 3 to 6 months of storage, the mois- ture content was still remained within 17%-20%, and the volume was decreased to 30%-40% of the original volume of fresh banana stems. This desiccation model made banana stems basically meet the requirements by drying storage. The plant- cutting down-crushing-compression-transportation-desiccation-storage production model was initially developed for desiccation and collection of banana stems, which would lay a certain foundation for the utilization of banana stem resource by enterprises.

Effects of the HMT on Nucleon Collective Flows within BUU Transport Model

Within the framework of a semiclassical Boltzmann-Uehling-Uhlenbeck （BUU） transport model, the high mo- mentum tail （HMT） effects of nucleon momentum distribution in the nucleus on the nucleon collective flows are studied in semieentral Au＋Au collisions. The HMT due to the isospin-dependent short-range correlations causes a smaller value of the collective flows. We find that the HMT effects on the nucleon collective flows are remarkable at beam energy of 300 MeV/nucleon and become weak as the incident beam energy increases. The results indicate that for the collective flow studies at intermediate energies, the HMT of nucleon momentum distribution in nucleus should be taken into account in transport models.

Study of Even ^(230-238)U Isotopes by Using Cranked Nilsson Model,Single Particle Schrodinger Fluid and Collective Model

The Cranking Nilsson model is applied to calculate the single-particle energy eigenvalues and eigenfunctions of nuclei in a strongly deformed potential. Accordingly, The L. D. Energy, the Strutinsky inertia, the L. D. inertia, the volume conservation factor , the smoothed energy, the BCS energy, the G-value and the electric quadrupole moment of the five uranium isotopes: 230U, 232U, 234U, 236U and 238U are calculated as functions of the deformation parameter. Furthermore, the single-particle Schrodinger fluid is applied to calculate the rigid-body model, the cranking-model and the equilibrium-model moments of inertia of the five uranium isotopes. Moreover, the collective model is applied to calculate the rotational energies of these isotopes. The best potential and deformation parameters are also given.

Comparative Phenomenological Description of Even-Even Isotopes at Mass Region A ≈ 70

In the present work the nuclear structure properties and the backbending phenomena of even-even isotopes at A ≈ 70 mass region are analyzed using two simultaneous theoretical models based on a simple modified version of the collective model predictions besides an improved version of exponential model with the inclusion of pairing correlation. In general, both models successfully describe the backbending phenomena in that region. From the comparison between the predictions of the two proposed models a firm conclusion is obtained concerning the superiority of the simple improved version of the exponential model in describing the forward and down-bending region of the φ-ω2 plots.

Critical point symmetry for odd-odd nuclei and collective multiple chiral doublet bands

A critical point symmetry(CPS) for odd-odd nuclei is built in the core-particle coupling scheme with the even-even core assumed to follow the spherical to triaxially deformed shape phase transition. It is shown that the model Hamiltonian can be approximately solved with the solutions being expressed in terms of the Bessel functions of irrational orders. In particular, the CPS predicts that collective multiple chiral doublets may exist in transitional odd-odd systems.

Geo-registered 3D models from crowdsourced image collections

In this article we present our system for scalable,robust,and fast city-scale reconstruction from Internet photo collections(IPC)obtaining geo-registered dense 3D models.The major achievements of our system are the efficient use of coarse appearance descriptors combined with strong geometric constraints to reduce the computational complexity of the image overlap search.This unique combination of recognition and geometric constraints allows our method to reduce from quadratic complexity in the number of images to almost linear complexity in the IPC size.Accordingly,our 3D-modeling framework is inherently better scalable than other state of the art methods and in fact is currently the only method to support modeling from millions of images.In addition,we propose a novel mechanism to overcome the inherent scale ambiguity of the reconstructed models by exploiting geo-tags of the Internet photo collection images and readily available StreetView panoramas for fully automatic geo-registration of the 3D model.Moreover,our system also exploits image appearance clustering to tackle the challenge of computing dense 3D models from an image collection that has significant variation in illumination between images along with a wide variety of sensors and their associated different radiometric camera parameters.Our algorithm exploits the redundancy of the data to suppress estimation noise through a novel depth map fusion.The fusion simultaneously exploits surface and free space constraints during the fusion of a large number of depth maps.Cost volume compression during the fusion achieves lower memory requirements for high-resolution models.We demonstrate our system on a variety of scenes from an Internet photo collection of Berlin containing almost three million images from which we compute dense models in less than the span of a day on a single computer.

Neutron-rich ^(104,106,108)Mo Isotopes in the Generalized Collective Model

The Generalized Collective Model (GCM) is applied to the even even neutron rich 104,106,108 Mo isotopes. With GCM the energy spectra, absolute B(E2) values, some B(E2) branching ratios and Potential Energy Surfaces (PES) for the 104,106,108 Mo isotopes are calculated. The PES of all these isotopes show a prolate minimum which becomes more pronounced in 106 Mo. The results are in agreement with the recent experimental report but are different from the viewpoint of the triaxial rotors, or γ soft deformation. Through a systematic study of PES, it is suggested that the even even neutron rich 104,106,108 Mo isotopes have prolate deformation.

Experimental study on filtration performance of the moving bed granular filter with axial flow

The filtration performance of the moving bed granular filter with axial flow (MBGF-AF) is investigated through a large cold experiment. The effect of different operation parameters on the filtration performance (collection efficiency, pressure drop) of the axial-flow moving bed filter is investigated in combination with the dust deposition effect and the mechanism of trapping dust by the capturing particles. The results show that the collection efficiency of MBGF-AF is enhanced by decreasing the superficial gas velocity, increasing the inlet dust concentration properly, or decreasing the moving velocity of the capturing particles. A model covering the above operation parameters is established to calculate the collection efficiency of the moving bed granular filter. It is used in a wide range of operating parameters for the MBGFs.

A primer on model selection using the Akaike Information Criterion

A powerful investigative tool in biology is to consider not a single mathematical model but a collection of models designed to explore different working hypotheses and select the best model in that collection.In these lecture notes,the usual workflow of the use of mathematical models to investigate a biological problem is described and the use of a collection of model is motivated.Models depend on parameters that must be estimated using observations;and when a collection of models is considered,the best model has then to be identified based on available observations.Hence,model calibration and selection,which are intrinsically linked,are essential steps of the workflow.Here,some procedures for model calibration and a criterion,the Akaike Information Criterion,of model selection based on experimental data are described.Rough derivation,practical technique of computation and use of this criterion are detailed.

Proton-induced current transient in SiGe HBT and charge collection model based on Monte Carlo simulation

The study presents an investigation into the proton-induced current transient in a silicon-germanium heterojunction bipolar transistor(SiGe HBT).The temporal information of the proton-induced current transients is first measured and then compared with results from heavy ion microbeam experiment.Additionally,a model for proton-induced charge collection based on Geant4 Monte Carlo simulation tools is constructed by using the information from heavy ion experiment and 3D TCAD simulation.The results obtained by the validated model exhibit good consistency with the proton experiment.

On the Distributions of Two Classes of Multiple Dependent Aggregate Claims

In this paper we examine two classes of correlated aggregate claims distributions, with univariate claim counts and multivariate claim sizes. Firstly, we extend the results of Hesselager [ASTIN Bulletin, 24： 19-32（1994）] and Wang ＆ Sobrero＇s [ASTIN Bulletin, 24：161-166 （1994）] concerning recursions for compound distributions to a multivariate situation where each claim event generates a random vector. Then we give a multivariate continuous version of recursive algorithm for calculating a family of compound distribution. Especially, to some extent, we obtain a continuous version of the corresponding results in Sundt [ASTIN Bulletin, 29：29-45 （1999）] and Ambagaspitiya [Insurance： Mathematics and Economics, 24：301-308 （1999）]. Finally, we give an example and show how to use the algorithm for aggregate claim distribution of first class to compute recursively the compound distribution.

Data collection model in hybrid network for participatory sensing

Advances in mobile technology make most people have their own mobile devices which contain various sensors such as a smartphone.People produce their own personal data or collect surrounding environment data with their mobile devices at every moment.Recently,a broad spectrum of studies on Participatory Sensing,the concept of extracting new knowledge from a mass of data sent by participants,are conducted.Data collection method is one of the base technologies for Participatory Sensing,so networking and data filtering techniques for collecting a large number of data are the most interested research area.In this paper,we propose a data collection model in hybrid network for participatory sensing.The proposed model classifies data into two types and decides networking form and data filtering method based on the data type to decrease loads on data center and improve transmission speed.