Abstract:
A class of second-order nonlinear impulsive integro-differential equations of mixed type whose principal part is given by time-varying generating operators in fractional power spaces is considered. We introduce the reasonable PC- -mild solution of second-order nonlinear impulsive integro-differential equations of mixed type and prove its existence. The existence of optimal controls for a Lagrange problem of systems governed by second-order nonlinear impulsive integro-equations of mixed type is also presented. An example is given for demonstration. 1. Introduction Some interesting models of mathematical biology or population, mechanics of materials, nuclear physics, and so forth, can be written in terms of second-order nonlinear partial integro-differential equations. This is the case of the model proposed to describe viscoelastic problems with memory. The system is given by where generates an evolution system in the parabolic case in Banach spaces (see [1–3]). , are nonlinear integral operators given by , , are nonlinear maps, and , . This represents the jump in the state , at time , respectively, with , determining the size of the jump at time . In fact, since the end of last century, impulsive evolution equations on infinite-dimensional spaces have been investigated by many authors including us. Particularly, Ahmed and we considered optimal control problems of systems governed by first-order impulsive evolution equations and first-order impulsive integro-differential equations [4–7]. Recently, we discussed the second-order impulsive evolution equations and the second-order impulsive integro-differential equations and their optimal controls in general Banach spaces [8–11]. In addition, to our knowledge, the second-order impulsive functional differential equations and the second-order impulsive integro-differential equations whose principal operator is bounded have been deeply studied by many authors [12–16]. However, the second-order impulsive integro-differential evolutions equations of mixed type whose principle operator is unbounded in infinite dimensional fractional power spaces and corresponding optimal control problems have not been extensively considered in the literature. Reducing the second-order evolution equations to the first-order evolution equations, we introduce a family of unbounded linear matrix operators , and prove that generates an evolution system which can be represented by , . Based on the evolution system , we introduce a reasonable PC-α-mild solution of (1.1). Using the interpolation space technique, we can overcome the

Abstract:
By using a linear scalarization method, we establish sufficient conditions for the H？lder continuity of the solution mappings to a parametric generalized vector quasiequilibrium problem with set-valued mappings. These results extend the recent ones in the recent literature, (e.g., Li et al. (2009), Li et al. (2011)). Furthermore, two examples are given to illustrate the obtained result.

Abstract:
Observational data show that the correlation between supermassive black holes (MBH) and galaxy bulge (Mbulge) masses follows a nearly linear trend, and that the correlation is strongest with the bulge rather than the total stellar mass (Mgal). With increasing redshift, the ratio Gamma=MBH/Mbulge relative to z=0 also seems to be larger for MBH >~ 10^{8.5} Msol. This study looks more closely at statistics to better understand the creation and observations of the MBH-Mbulge correlation. It is possible to show that if galaxy merging statistics can drive the correlation, minor mergers are responsible for causing a *convergence to linearity* most evident at high masses, whereas major mergers have a central limit convergence that more strongly *reduces the scatter*. This statistical reasoning is agnostic about galaxy morphology. Therefore, combining statistical prediction (more major mergers ==> tighter correlation) with observations (bulges = tightest correlation), would lead one to conclude that more major mergers (throughout an entire merger tree, not just the primary branch) give rise to more prominent bulges. With regard to controversial findings that Gamma increases with redshift, this study shows why the luminosity function (LF) bias argument, taken correctly at face value, strengthens rather than weakens the results. However, correcting for LF bias is unwarranted because the BH mass scale for quasars is bootstrapped to the MBH-Sigma* correlation in normal galaxies at z=0, and quasar-quasar comparisons are internally consistent. In Monte-Carlo simulations, high Gamma objects are "under-merged" galaxies that take longer to converge to linearity via minor mergers. Another evidence that the galaxies are undermassive at z >~ 2 for their MBH is that the quasar hosts are very compact for their expected mass.

Abstract:
The double nucleus geometry of M31 is currently best explained by the eccentric disk hypothesis of Tremaine, but whether the eccentric disk resulted from the tidal disruption of an inbounding star cluster by a nuclear black hole, or by an m=1 perturbation of a native nuclear disk, remains debatable. I perform detailed 2-D decomposition of the M31 double nucleus in the Hubble Space Telescope V-band to study the bulge structure and to address competing formation scenarios of the eccentric disk. I deblend the double nucleus (P1 and P2) and the bulge simultaneously using five Sersic and one Nuker components. P1 and P2 appear to be embedded inside an intermediate component (r_e=3.2") that is nearly spherical (q=0.97+/-m0.02), while the main galaxy bulge is more elliptical (q=0.81+/-0.01). The spherical bulge mass of 2.8x10^7 M_sol is comparable to the supermassive black hole mass (3x10^7 M_sol). In the 2-D decomposition, the bulge is consistent with being centered near the UV peak of P2, but the exact position is difficult to pinpoint because of dust in the bulge. P1 and P2 are comparable in mass. Within a radius r=1\arcsec of P2, the relative mass fraction of the nuclear components is M_BH:M_bulge:P1: P2 = 4.3:1.2:1:0.7, assuming the luminous components have a common mass-to-light ratio of 5.7. The eccentric disk as a whole (P1+P2) is massive, M ~ 2.1x10^7 M_sol, comparable to the black hole and the local bulge mass. As such, the eccentric disk could not have been formed entirely out of stars that were stripped from an inbounding star cluster. Hence, the more favored scenario is that of a disk formed in situ by an m=1 perturbation, caused possibly by the passing of a giant molecular cloud, or the passing/accretion of a small globular cluster.

Dynamic
monitoring of plant cover and soil erosion often uses remote sensing data,
especially for estimating the plant cover rate (vegetation coverage) by
vegetation index. However, the latter is influenced by atmospheric effects and
methods for correcting them are still imperfect and disputed. This research
supposed and practiced an indirect, fast, and operational method to conduct
atmospheric correction of images for getting comparable vegetation index values
in different times. It tries to find a variable free from atmospheric effects,
e.g., the mean vegetation coverage value of the whole study area, as a basis to
reduce atmospheric correction parameters by establishing mathematical models
and conducting simulation calculations. Using these parameters, the images can
be atmospherically corrected. And then, the vegetation index and corresponding
vegetation coverage values for all pixels, the vegetation coverage maps and
coverage grade maps for different years were calculated, i.e., the plant cover monitoring was realized. Using the vegetation
coverage grade maps and the ground slope grade map from a DEM to generate soil
erosion grade maps for different years, the soil erosion monitoring was also
realized. The results show that in the study area the vegetation coverage was
the lowest in 1976, much better in 1989, but a bit worse again in 2001. Towards
the soil erosion, it had been mitigated continuously from 1976 to 1989 and then
to 2001. It is interesting that a little decrease of vegetation coverage from
1989 to 2001 did not lead to increase of soil erosion. The reason is that the
decrease of vegetation coverage was chiefly caused by urbanization and thus
mainly occurred in very gentle terrains, where soil erosion was naturally
slight. The results clearly indicate the details of plant cover and soil
erosion change in 25 years and also offer a scientific foundation for plant
and soil conservation.

Abstract:
our objective was to clone, express and characterize adult dermatophagoides farinae group 1 (der f 1) allergens to further produce recombinant allergens for future clinical applications in order to eliminate side reactions from crude extracts of mites. based on genbank data, we designed primers and amplified the cdna fragment coding for der f 1 by nested-pcr. after purification and recovery, the cdna fragment was cloned into the pmd19-t vector. the fragment was then sequenced, subcloned into the plasmid pet28a(+), expressed in escherichia coli bl21 and identified by western blotting. the cdna coding for der f 1 was cloned, sequenced and expressed successfully. sequence analysis showed the presence of an open reading frame containing 966 bp that encodes a protein of 321 amino acids. interestingly, homology analysis showed that the der p 1 shared more than 87% identity in amino acid sequence with eur m 1 but only 80% with der f 1. furthermore, phylogenetic analyses suggested that d. pteronyssinus was evolutionarily closer to euroglyphus maynei than to d. farinae, even though d. pteronyssinus and d. farinae belong to the same dermatophagoides genus. a total of three cysteine peptidase active sites were found in the predicted amino acid sequence, including 127-138 (qggcgscwafsg), 267-277 (nyhavnivgyg) and 284-303 (ywivrnswdttwgdsgygyf). moreover, secondary structure analysis revealed that der f 1 contained an a helix (33.96%), an extended strand (17.13%), a ？ turn (5.61%), and a random coil (43.30%). a simple three-dimensional model of this protein was constructed using a swiss-model server. the cdna coding for der f 1 was cloned, sequenced and expressed successfully. alignment and phylogenetic analysis suggests that d. pteronyssinus is evolutionarily more similar to e. maynei than to d. farinae.

This paper presents a new
noninvasive blood glucose monitoring method based on four near infrared
spectrums and double artificial neural network analysis. We choose four near
infrared wavelengths, 820 nm, 875 nm, 945 nm, 1050 nm, as transmission
spectrums, and capture four fingers transmission PPG signals simultaneously.
The wavelet transform algorithm is used to remove baseline drift, smooth
signals and extract eight eigenvalues of each PPG signal. The eigenvalues are
the input parameters of double artificial neural network analysis model. Double
artificial neural network regression combines the classification recognition
algorithm with prediction algorithm to improve the accuracy of measurement.
Experiments show that the root mean square error of the prediction is between
0.97 mg/dL - 6.69 mg/dL, the average of root mean square error is 3.80 mg/dL.

Abstract:
Under new assumptions, we provide suffcient conditions for the (upper and lower) semicontinuity and continuity of the solution mappings to a class of generalized parametric set-valued Ky Fan inequality problems in linear metric space. These results extend and improve some known results in the literature (e.g., Gong, 2008; Gong and Yoa, 2008; Chen and Gong, 2010; Li and Fang, 2010). Some examples are given to illustrate our results.

Abstract:
We identified gene coexpression networks in the transcriptome of developing Arabidopsis (Arabidopsis thaliana) seeds from the globular to mature embryo stages by analyzing publicly accessible microarray datasets. Genes encoding the known enzymes in the fatty acid biosynthesis pathway were found in one coexpression subnetwork (or cluster), while genes encoding oleosins and seed storage proteins were identified in another subnetwork with a distinct expression profile. In the triacylglycerol assembly pathway, only the genes encoding diacylglycerol acyltransferase 1 (DGAT1) and a putative cytosolic "type 3" DGAT exhibited a similar expression pattern with genes encoding oleosins. We also detected a large number of putative cis-acting regulatory elements in the promoter regions of these genes, and promoter motifs for LEC1 (LEAFY COTYLEDON 1), DOF (DNA-binding-with-One-Finger), GATA, and MYB transcription factors (TF), as well as SORLIP5 (Sequences Over-Represented in Light-Induced Promoters 5), are overrepresented in the promoter regions of fatty acid biosynthetic genes. The conserved CCAAT motifs for B3-domain TFs and binding sites for bZIP (basic-leucine zipper) TFs are enriched in the promoters of genes encoding oleosins and seed storage proteins.Genes involved in the accumulation of seed storage reserves are expressed in distinct patterns and regulated by different TFs. The gene coexpression clusters and putative regulatory elements presented here provide a useful resource for further experimental characterization of protein interactions and regulatory networks in this process.Seed storage reserves accumulated during embryogenesis in higher plants are crucial for plant propagation, providing carbon and energy during germination prior to seedling establishment. In mature Arabidopsis seeds, storage lipids and proteins are the major storage compounds, each accounting for 30% - 45% of the seed dry weight [1]. The past decade has witnessed a substantial progress in identi

Abstract:
A new size-resolved dust scheme based on the numerical method of piecewise log-normal approximation (PLA) was developed and implemented in the fourth generation of the Canadian Atmospheric Global Climate Model with the PLA Aerosol Model (CanAM4-PAM). The total simulated annual global dust emission is 2500 Tg yr 1, and the dust mass load is 19.3 Tg for year 2000. Both are consistent with estimates from other models. Results from simulations are compared with multiple surface measurements near and away from dust source regions, validating the generation, transport and deposition of dust in the model. Most discrepancies between model results and surface measurements are due to unresolved aerosol processes. Biases in long-range transport are also contributing. Radiative properties of dust aerosol are derived from approximated parameters in two size modes using Mie theory. The simulated aerosol optical depth (AOD) is compared with satellite and surface remote sensing measurements and shows general agreement in terms of the dust distribution around sources. The model yields a dust AOD of 0.042 and dust aerosol direct radiative forcing (ADRF) of 1.24 W m 2 respectively, which show good consistency with model estimates from other studies.