Approximation of Rough Functions

For given $p\in\lbrack1,\infty]$ and $g\in L^{p}\mathbb{(R)}$, we establish the existence and uniqueness of solutions $f\in L^{p}(\mathbb{R)}$, to the equation $$f(x)-af(bx)=g(x),$$ where $a\in\mathbb{R}$, $b\in\mathbb{R} \setminus \{0\}$, and $\left\vert a\right\vert \neq\left\vert b\right\vert ^{1/p}$. Solutions include well-known nowhere differentiable functions such as those of Bolzano, Weierstrass, Hardy, and many others. Connections and consequences in the theory of fractal interpolation, approximation theory, and Fourier analysis are established.Comment: 16 pages, 3 figure

On the non-existence of an R-labeling

We present a family of Eulerian posets which does not have any R-labeling. The result uses a structure theorem for R-labelings of the butterfly poset.Comment: 6 pages, 1 figure. To appear in the journal Orde

AN ECONOMIC ANALYSIS OF A CORN-SOYBEAN CROP ROTATION UNDER VARIOUS INPUT COMBINATIONS IN SOUTH CENTRAL TEXAS

Eight input combinations of commercial fertilizer, insecticides, and herbicides on a corn-soybean crop rotation in the Brazos River Bottom of Texas are evaluated. Input combinations which do not fully utilize all three inputs are consistently ranked higher by all criteria as the preferred input strategy for the corn-soybean rotation system. These results, which indicate limited input crop rotations that fall somewhere between the extremes of conventional agricultural production and organic agriculture, deserve further attention as a possible production alternative.corn, limited input, soybean, Crop Production/Industries,

Block Coordinate Descent for Sparse NMF

Nonnegative matrix factorization (NMF) has become a ubiquitous tool for data analysis. An important variant is the sparse NMF problem which arises when we explicitly require the learnt features to be sparse. A natural measure of sparsity is the L$_0$ norm, however its optimization is NP-hard. Mixed norms, such as L$_1$/L$_2$ measure, have been shown to model sparsity robustly, based on intuitive attributes that such measures need to satisfy. This is in contrast to computationally cheaper alternatives such as the plain L$_1$ norm. However, present algorithms designed for optimizing the mixed norm L$_1$/L$_2$ are slow and other formulations for sparse NMF have been proposed such as those based on L$_1$ and L$_0$ norms. Our proposed algorithm allows us to solve the mixed norm sparsity constraints while not sacrificing computation time. We present experimental evidence on real-world datasets that shows our new algorithm performs an order of magnitude faster compared to the current state-of-the-art solvers optimizing the mixed norm and is suitable for large-scale datasets

Intrinsically Disordered C-Terminal Tails of \u3cem\u3eE. coli\u3c/em\u3e Single-Stranded DNA Binding Protein Regulate Cooperative Binding to Single-Stranded DNA

The homotetrameric Escherichia coli single-stranded DNA binding protein (SSB) plays a central role in DNA replication, repair and recombination. E. coli SSB can bind to long single-stranded DNA (ssDNA) in multiple binding modes using all four subunits [(SSB)65 mode] or only two subunits [(SSB)35 binding mode], with the binding mode preference regulated by salt concentration and SSB binding density. These binding modes display very different ssDNA binding properties with the (SSB)35 mode displaying highly cooperative binding to ssDNA. SSB tetramers also bind an array of partner proteins, recruiting them to their sites of action. This is achieved through interactions with the last 9 amino acids (acidic tip) of the intrinsically disordered linkers (IDLs) within the four C-terminal tails connected to the ssDNA binding domains. Here, we show that the amino acid composition and length of the IDL affects the ssDNA binding mode preferences of SSB protein. Surprisingly, the number of IDLs and the lengths of individual IDLs together with the acidic tip contribute to highly cooperative binding in the (SSB)35 binding mode. Hydrodynamic studies and atomistic simulations suggest that the E. coli SSB IDLs show a preference for forming an ensemble of globular conformations, whereas the IDL from Plasmodium falciparum SSB forms an ensemble of more extended random coils. The more globular conformations correlate with cooperative binding

Analisis Faktor-faktor yang Mempengaruhi Kinerja Pemerintah Daerah (Study Empiris pada Skpd Kabupaten Indragiri Hulu)

This study aimed to examine the influence of the good government, internal control, organization culture, leadership style, organization commitment on governance performance. The population in this study were employed who worked in the SKPD Kabupaten Indragiri Hulu (30 government agencies). The sampling method used in this study is proportioned stratified random sampling method. The respondent in this study is the employee Eselon III and Eselon IV SKPD,. The sample used in this study were 100 respondents. The hypotheses then tested is multiple linear regression analysis by using SPSS version 20.0. The result of this study indicated that the good governance, internal control, leadership style, organization commitment has significantly effect on local government performence. Whereas the organizational culture does not affect the performance of local governments. The magnitude of the effect (R2) the good governance, internal control, organization culture, leadership style, organization commitment, the performance of local governments was ,53%. While the remaining 47% is influenced by other independent variabel that are not observed in this study.Keywords: good government, internal control, organization culture, leadership style, organization commitment

Modular Organization of Functional Network Connectivity in Healthy Controls and Patients with Schizophrenia during the Resting State

Neuroimaging studies have shown that functional brain networks composed from select regions of interest have a modular community structure. However, the organization of functional network connectivity (FNC), comprising a purely data-driven network built from spatially independent brain components, is not yet clear. The aim of this study is to explore the modular organization of FNC in both healthy controls (HCs) and patients with schizophrenia (SZs). Resting state functional magnetic resonance imaging data of HCs and SZs were decomposed into independent components (ICs) by group independent component analysis (ICA). Then weighted brain networks (in which nodes are brain components) were built based on correlations between ICA time courses. Clustering coefficients and connectivity strength of the networks were computed. A dynamic branch cutting algorithm was used to identify modules of the FNC in HCs and SZs. Results show stronger connectivity strength and higher clustering coefficient in HCs with more and smaller modules in SZs. In addition, HCs and SZs had some different hubs. Our findings demonstrate altered modular architecture of the FNC in schizophrenia and provide insights into abnormal topological organization of intrinsic brain networks in this mental illness