Evolution of the Galaxy - Dark Matter Connection and the Assembly of Galaxies in Dark Matter Halos

We present a new model to describe the galaxy-dark matter connection across cosmic time, which unlike the popular subhalo abundance matching technique is self-consistent in that it takes account of the facts that (i) subhalos are accreted at different times, and (ii) the properties of satellite galaxies may evolve after accretion. Using observations of galaxy stellar mass functions out to $z \sim 4$, the conditional stellar mass function at $z\sim 0.1$ obtained from SDSS galaxy group catalogues, and the two-point correlation function (2PCF) of galaxies at $z \sim 0.1$ as function of stellar mass, we constrain the relation between galaxies and dark matter halos over the entire cosmic history from $z \sim 4$ to the present. This relation is then used to predict the median assembly histories of different stellar mass components within dark matter halos (central galaxies, satellite galaxies, and halo stars). We also make predictions for the 2PCFs of high-$z$ galaxies as function of stellar mass. Our main findings are the following: (i) Our model reasonably fits all data within the observational uncertainties, indicating that the $\Lambda$CDM concordance cosmology is consistent with a wide variety of data regarding the galaxy population across cosmic time. (ii) ... [abridged]Comment: 37pages, 20 figures, major revision, data updated to SDSS DR7, main conclusions remain unchange

Internal kinematics of groups of galaxies in the Sloan Digital Sky Survey data release 7

We present measurements of the velocity dispersion profile (VDP) for galaxy groups in the final data release of the Sloan Digital Sky Survey (SDSS). For groups of given mass we estimate the redshift-space cross-correlation function (CCF) with respect to a reference galaxy sample, xi(r_p, pi), the projected CCF, w_p(r_p), and the real-space CCF, xi(r). The VDP is then extracted from the redshift distortion in xi(r_p, pi), by comparing xi(r_p, pi) with xi(r). We find that the velocity dispersion (VD) within virial radius (R_200) shows a roughly flat profile, with a slight increase at radii below ~0.3 R_200 for high mass systems. The average VD within the virial radius, sigma_v, is a strongly increasing function of central galaxy mass. We apply the same methodology to N-body simulations with the concordance Lambda cold dark matter cosmology but different values of the density fluctuation parameter sigma_8, and we compare the results to the SDSS results. We show that the sigma_v-M_* relation from the data provides stringent constraints on both sigma_8 and sigma_ms, the dispersion in log M_* of central galaxies at fixed halo mass. Our best-fitting model suggests sigma_8 = 0.86 +/- 0.03 and sigma_ms = 0.16 +/- 0.03. The slightly higher value of sigma_8 compared to the WMAP7 result might be due to a smaller matter density parameter assumed in our simulations. Our VD measurements also provide a direct measure of the dark matter halo mass for central galaxies of different luminosities and masses, in good agreement with the results obtained by Mandelbaum et al. (2006) from stacking the gravitational lensing signals of the SDSS galaxies.Comment: 17 pages, 10 figures, 1 table, accepted for publication in ApJ, text slightly changed, abstract substantially shortened, two new panels added to Figs. 2 and 3 showing w_p and VDP as functions of r_p/R_200 instead of r_

Perovskite-polymer composite cross-linker approach for highly-stable and efficient perovskite solar cells.

Manipulation of grain boundaries in polycrystalline perovskite is an essential consideration for both the optoelectronic properties and environmental stability of solar cells as the solution-processing of perovskite films inevitably introduces many defects at grain boundaries. Though small molecule-based additives have proven to be effective defect passivating agents, their high volatility and diffusivity cannot render perovskite films robust enough against harsh environments. Here we suggest design rules for effective molecules by considering their molecular structure. From these, we introduce a strategy to form macromolecular intermediate phases using long chain polymers, which leads to the formation of a polymer-perovskite composite cross-linker. The cross-linker functions to bridge the perovskite grains, minimizing grain-to-grain electrical decoupling and yielding excellent environmental stability against moisture, light, and heat, which has not been attainable with small molecule defect passivating agents. Consequently, all photovoltaic parameters are significantly enhanced in the solar cells and the devices also show excellent stability

Moisture Content Prediction Below and Above Fiber Saturation Point by Partial Least Squares Regression Analysis on Near Infrared Absorption Spectra of Korean Pine

This study was performed to predict the surface moisture content of Korean pine (Pinus koraiensis) with low moisture content (approximately 0%) and high moisture content above the FSP using near IR spectroscopy. Near IR absorbance spectra of circular specimens were acquired at various moisture contents at 25°C. To enhance the precision of the regression model, mathematical preprocessing was performed by determining the three-point moving average and Norris second derivatives. After preprocessing, partial least squares regression was carried out to establish the surface moisture content prediction model. We divided the specimens into two groups based on their moisture contents. For the first group, which possessed moisture contents less than 30%, the R2 values and root mean squared error of prediction (RMSEP) of the model were 0.96 and 1.48, respectively. For the second group, which possessed moisture contents greater than 30%, the R2 values and RMSEP of the model were 0.94 and 4.88, respectively. For all moisture contents, the R2 and RMSEP were 0.96 and 5.15, respectively. As the range of moisture contents included in the prediction model was expanded, the error of the model increased. In addition, the peak positions of the water absorption band (1440 and 1930 nm) shifted to longer wavelengths at higher moisture contents

Optimization of the Aedes aegypti Control Strategies for Integrated Vector Management

We formulate an infinite-time quadratic functional minimization problem of Aedes aegypti mosquito population. Three techniques of mosquito population management, chemical insecticide control, sterile insect technique control, and environmental carrying capacity reduction, are combined in order to obtain the most sustainable strategy to reduce mosquito population and consequently dengue disease. The solution of the optimization control problem is based on the ideas of the Dynamic Programming and Lyapunov Stability using State-Dependent Riccati Equation (SDRE) control method. Different scenarios are analyzed combining three mentioned population management efforts in order to assess the most sustainable policy to reduce the mosquito population

HiHGNN: Accelerating HGNNs through Parallelism and Data Reusability Exploitation

Heterogeneous graph neural networks (HGNNs) have emerged as powerful algorithms for processing heterogeneous graphs (HetGs), widely used in many critical fields. To capture both structural and semantic information in HetGs, HGNNs first aggregate the neighboring feature vectors for each vertex in each semantic graph and then fuse the aggregated results across all semantic graphs for each vertex. Unfortunately, existing graph neural network accelerators are ill-suited to accelerate HGNNs. This is because they fail to efficiently tackle the specific execution patterns and exploit the high-degree parallelism as well as data reusability inside and across the processing of semantic graphs in HGNNs. In this work, we first quantitatively characterize a set of representative HGNN models on GPU to disclose the execution bound of each stage, inter-semantic-graph parallelism, and inter-semantic-graph data reusability in HGNNs. Guided by our findings, we propose a high-performance HGNN accelerator, HiHGNN, to alleviate the execution bound and exploit the newfound parallelism and data reusability in HGNNs. Specifically, we first propose a bound-aware stage-fusion methodology that tailors to HGNN acceleration, to fuse and pipeline the execution stages being aware of their execution bounds. Second, we design an independency-aware parallel execution design to exploit the inter-semantic-graph parallelism. Finally, we present a similarity-aware execution scheduling to exploit the inter-semantic-graph data reusability. Compared to the state-of-the-art software framework running on NVIDIA GPU T4 and GPU A100, HiHGNN respectively achieves an average 41.5$\times$ and 8.6$\times$ speedup as well as 106$\times$ and 73$\times$ energy efficiency with quarter the memory bandwidth of GPU A100

Identifikasi Dan Problematika Penggunaan Lahan Lingkungan Bantaran Sungai Terhadap Peraturan Pemerintah Dan Daerah Di Kota Banjarmasin

AIMS:The role of adoptive immunotherapy (AIT) for patients with hepatocellular carcinoma (HCC) who have received curative therapy is still not well illustrated. This timely meta-analysis aims to update the current evidence on efficacy and safety of AIT for patients with HCC who have received curative therapy. METHODS:We searched PubMed, EMBASE, Scopus and the Cochrane Library Through January 2017 for relevant studies. Mortality and tumor recurrence were compared between patients with or without adjuvant AIT. The meta-analysis was performed using Review Manager 5.3. RESULTS:Eight studies involving 1861 patients met the eligibility criteria and were meta-analyzed. Adjuvant AIT was associated with significantly lower mortality at 1 year (RR 0.64, 95%CI 0.52-0.79), 3 years (RR 0.73, 95%CI 0.65-0.81) and 5 years (RR 0.86, 95%CI 0.79-0.94). Similarly, adjuvant AIT was associated with significantly lower recurrence rate than curative therapies alone at 1 year (RR 0.64, 95%CI 0.49-0.82), 3 years (RR 0.85, 95%CI 0.79-0.91) and 5 years (RR 0.90, 95%CI 0.85-0.95). Short-term outcomes were confirmed in sensitivity analyses based on randomized trials or choice of random- or fixed-effect meta-analysis model. None of the included patients experienced grade 4 adverse events. CONCLUSIONS:This timely meta-analysis confirms the evidence that adjuvant AIT for patients with HCC after curative treatment lowers risk of mortality and tumor recurrence