Data-Driven Understanding of Smart Service Systems Through Text Mining

Smart service systems are everywhere, in homes and in the transportation, energy, and healthcare sectors. However, such systems have yet to be fully understood in the literature. Given the widespread applications of and research on smart service systems, we used text mining to develop a unified understanding of such systems in a data-driven way. Specifically, we used a combination of metrics and machine learning algorithms to preprocess and analyze text data related to smart service systems, including text from the scientific literature and news articles. By analyzing 5,378 scientific articles and 1,234 news articles, we identify important keywords, 16 research topics, 4 technology factors, and 13 application areas. We define ???smart service system??? based on the analytics results. Furthermore, we discuss the theoretical and methodological implications of our work, such as the 5Cs (connection, collection, computation, and communications for co-creation) of smart service systems and the text mining approach to understand service research topics. We believe this work, which aims to establish common ground for understanding these systems across multiple disciplinary perspectives, will encourage further research and development of modern service systems

Generation and physiological roles of linear ubiquitin chains

Ubiquitination now ranks with phosphorylation as one of the best-studied post-translational modifications of proteins with broad regulatory roles across all of biology. Ubiquitination usually involves the addition of ubiquitin chains to target protein molecules, and these may be of eight different types, seven of which involve the linkage of one of the seven internal lysine (K) residues in one ubiquitin molecule to the carboxy-terminal diglycine of the next. In the eighth, the so-called linear ubiquitin chains, the linkage is between the amino-terminal amino group of methionine on a ubiquitin that is conjugated with a target protein and the carboxy-terminal carboxy group of the incoming ubiquitin. Physiological roles are well established for K48-linked chains, which are essential for signaling proteasomal degradation of proteins, and for K63-linked chains, which play a part in recruitment of DNA repair enzymes, cell signaling and endocytosis. We focus here on linear ubiquitin chains, how they are assembled, and how three different avenues of research have indicated physiological roles for linear ubiquitination in innate and adaptive immunity and suppression of inflammation

The Prognostic Value of Non-Linear Analysis of Heart Rate Variability in Patients with Congestive Heart Failure—A Pilot Study of Multiscale Entropy

AIMS: The influences of nonstationarity and nonlinearity on heart rate time series can be mathematically qualified or quantified by multiscale entropy (MSE). The aim of this study is to investigate the prognostic value of parameters derived from MSE in the patients with systolic heart failure. METHODS AND RESULTS: Patients with systolic heart failure were enrolled in this study. One month after clinical condition being stable, 24-hour Holter electrocardiogram was recording. MSE as well as other standard parameters of heart rate variability (HRV) and detrended fluctuation analysis (DFA) were assessed. A total of 40 heart failure patients with a mea age of 56±16 years were enrolled and followed-up for 684±441 days. There were 25 patients receiving β-blockers treatment. During follow-up period, 6 patients died or received urgent heart transplantation. The short-term exponent of DFA and the slope of MSE between scale 1 to 5 were significantly different between patients with or without β-blockers (p = 0.014 and p = 0.028). Only the area under the MSE curve for scale 6 to 20 (Area(6-20)) showed the strongest predictive power between survival (n = 34) and mortality (n = 6) groups among all the parameters. The value of Area(6-20)21.2 served as a significant predictor of mortality or heart transplant (p = 0.0014). CONCLUSION: The area under the MSE curve for scale 6 to 20 is not relevant to β-blockers and could further warrant independent risk stratification for the prognosis of CHF patients

Probing Specific Interaction Forces Between Human IgG and Rat Anti-Human IgG by Self-Assembled Monolayer and Atomic Force Microscopy

Interaction forces between biological molecules such as antigen and antibody play important roles in many biological processes, but probing these forces remains technically challenging. Here, we investigated the specific interaction and unbinding forces between human IgG and rat anti-human IgG using self assembled monolayer (SAM) method for sample preparation and atomic force microscopy (AFM) for interaction force measurement. The specific interaction force between human IgG and rat anti-human IgG was found to be 0.6–1.0 nN, and the force required for unbinding a single pair of human IgG and rat anti-human IgG was calculated to be 144 ± 11 pN. The results are consistent with those reported in the literatures. Therefore, SAM for sample preparation combined with AFM for interaction measurement is a relatively simple, sensitive and reliable technique to probe specific interactions between biological molecules such as antigen and antibody

Relationship between morphological features and kinetic patterns of enhancement of the dynamic breast magnetic resonance imaging and clinico-pathological and biological factors in invasive breast cancer

<p>Abstract</p> <p>Background</p> <p>To investigate the relationship between the magnetic resonance imaging (MRI) features of breast cancer and its clinicopathological and biological factors.</p> <p>Methods</p> <p>Dynamic MRI parameters of 68 invasive breast carcinomas were investigated. We also analyzed microvessel density (MVD), estrogen and progesterone receptor status, and expression of p53, HER2, ki67, VEGFR-1 and 2.</p> <p>Results</p> <p>Homogeneous enhancement was significantly associated with smaller tumor size (T1: < 2 cm) (p = 0.015). Tumors with irregular or spiculated margins had a significantly higher MVD than tumors with smooth margins (p = 0.038). Tumors showing a maximum enhancement peak at two minutes, or longer, after injecting the contrast, had a significantly higher MVD count than those which reached this point sooner (p = 0.012). The percentage of tumors with vascular invasion or high mitotic index was significantly higher among those showing a low percentage (≤ 150%) of maximum enhancement before two minutes than among those ones showing a high percentage (>150%) of enhancement rate (p = 0.016 and p = 0.03, respectively). However, there was a significant and positive association between the mitotic index and the peak of maximum intensity (p = 0.036). Peritumor inflammation was significantly associated with washout curve type III (p = 0.042).</p> <p>Conclusions</p> <p>Variations in the early phase of dynamic MRI seem to be associated with parameters indicatives of tumor aggressiveness in breast cancer.</p

Radio emission from Supernova Remnants

The explosion of a supernova releases almost instantaneously about 10^51 ergs of mechanic energy, changing irreversibly the physical and chemical properties of large regions in the galaxies. The stellar ejecta, the nebula resulting from the powerful shock waves, and sometimes a compact stellar remnant, constitute a supernova remnant (SNR). They can radiate their energy across the whole electromagnetic spectrum, but the great majority are radio sources. Almost 70 years after the first detection of radio emission coming from a SNR, great progress has been achieved in the comprehension of their physical characteristics and evolution. We review the present knowledge of different aspects of radio remnants, focusing on sources of the Milky Way and the Magellanic Clouds, where the SNRs can be spatially resolved. We present a brief overview of theoretical background, analyze morphology and polarization properties, and review and critical discuss different methods applied to determine the radio spectrum and distances. The consequences of the interaction between the SNR shocks and the surrounding medium are examined, including the question of whether SNRs can trigger the formation of new stars. Cases of multispectral comparison are presented. A section is devoted to reviewing recent results of radio SNRs in the Magellanic Clouds, with particular emphasis on the radio properties of SN 1987A, an ideal laboratory to investigate dynamical evolution of an SNR in near real time. The review concludes with a summary of issues on radio SNRs that deserve further study, and analyzing the prospects for future research with the latest generation radio telescopes.Comment: Revised version. 48 pages, 15 figure

Chromo- and Fluorogenic Organometallic Sensors

Compounds that change their absorption and/or emission properties in the presence of a target ion or molecule have been studied for many years as the basis for optical sensing. Within this group of compounds, a variety of organometallic complexes have been proposed for the detection of a wide range of analytes such as cations (including H+), anions, gases (e.g. O 2, SO2, organic vapours), small organic molecules, and large biomolecules (e.g. proteins, DNA). This chapter focuses on work reported within the last few years in the area of organometallic sensors. Some of the most extensively studied systems incorporate metal moieties with intense long-lived metal-to-ligand charge transfer (MLCT) excited states as the reporter or indicator unit, such as fac-tricarbonyl Re(I) complexes, cyclometallated Ir(III) species, and diimine Ru(II) or Os(II) derivatives. Other commonly used organometallic sensors are based on Pt-alkynyls and ferrocene fragments. To these reporters, an appropriate recognition or analyte-binding unit is usually attached so that a detectable modification on the colour and/or the emission of the complex occurs upon binding of the analyte. Examples of recognition sites include macrocycles for the binding of cations, H-bonding units selective to specific anions, and DNA intercalating fragments. A different approach is used for the detection of some gases or vapours, where the sensor's response is associated with changes in the crystal packing of the complex on absorption of the gas, or to direct coordination of the analyte to the metal centre

Applying Harmonic Optical Microscopy for Spatial Alignment of Atrial Collagen Fibers

BACKGROUND: Atrial fibrosis creates a vulnerable tissue for atrial fibrillation (AF), but the spatial disarray of collagen fibers underlying atrial fibrosis is not fully elucidated. OBJECTIVE: This study hypothesizes that harmonics optical microscopy can illuminate the spatial mal-alignment of collagen fibers in AF via a layer-by-layer approach. PATIENTS AND METHODS: Atrial tissues taken from patients who underwent open-heart surgery were examined by harmonics optical microscopy. Using the two-dimensional Fourier transformation method, a spectral-energy description of image texture was constituted and its entropy was used to quantify the mal-alignment of collagen fibers. The amount of collagen fiber was derived from its area ratio to total atrial tissue in each image. Serum C-terminal pro-collagen pro-peptide (CICP), pro-matrix metalloproteinase-1 (pro-MMP-1), and tissue inhibitor of matrix metalloproteinase-1 (TIMP-1) were also evaluated. RESULTS: 46 patients were evaluated, including 20 with normal sinus rhythm and 26 with AF. The entropy of spectral-energy distribution of collagen alignment was significantly higher in AF than that in sinus rhythm (3.97 ± 0.33 vs. 2.80 ± 0.18, p<0.005). This difference was more significant in the permanent AF group. The amount of collagen was also significantly higher in AF patients (0.39 ± 0.13 vs. 0.18 ± 0.06, p<0.005) but serum markers of cardiac fibrosis were not significantly different between the two groups. CONCLUSIONS: Harmonics optical microscopy can quantify the spatial mal-alignment of collagen fibers in AF. The entropy of spectral-energy distribution of collagen alignment is a potential tool for research in atrial remodeling

Measurement of the Bottom-Strange Meson Mixing Phase in the Full CDF Data Set

We report a measurement of the bottom-strange meson mixing phase \beta_s using the time evolution of B0_s -> J/\psi (->\mu+\mu-) \phi (-> K+ K-) decays in which the quark-flavor content of the bottom-strange meson is identified at production. This measurement uses the full data set of proton-antiproton collisions at sqrt(s)= 1.96 TeV collected by the Collider Detector experiment at the Fermilab Tevatron, corresponding to 9.6 fb-1 of integrated luminosity. We report confidence regions in the two-dimensional space of \beta_s and the B0_s decay-width difference \Delta\Gamma_s, and measure \beta_s in [-\pi/2, -1.51] U [-0.06, 0.30] U [1.26, \pi/2] at the 68% confidence level, in agreement with the standard model expectation. Assuming the standard model value of \beta_s, we also determine \Delta\Gamma_s = 0.068 +- 0.026 (stat) +- 0.009 (syst) ps-1 and the mean B0_s lifetime, \tau_s = 1.528 +- 0.019 (stat) +- 0.009 (syst) ps, which are consistent and competitive with determinations by other experiments.Comment: 8 pages, 2 figures, Phys. Rev. Lett 109, 171802 (2012