Wear Characteristics of a Laser Surface Alloyed Al-Mg-Si with Co Alloy Powder

The microstructure and wear resistance of a laser surface alloyed Al-Mg-Si with Co alloy powder were investigated. The experimental results indicate that a porosity-free zone can be generated but some cracks appear after laser surface alloying (LSA). In this investigation, two regions, A (surface region) and B (bottom region), are observed in the pool. Al 9 Co 2 particles with a network structure are present in region A and block-like Al 13 Co 4 particles are distributed in region B. The hardness of the LSA specimens is three to nine times higher than that of the Almatrix. The high hardness of LSA specimens cause them to exhibit excellent sliding wear performance so they have a lower friction coefficient and wear rate. Notably, the critical temperature of the sliding wear resistance of the LSA specimen exceeds that of the Al-matrix by approximately 50 K

A New On-Land Seismogenic Structure Source Database from the Taiwan Earthquake Model (TEM) Project for Seismic Hazard Analysis of Taiwan

Taiwan is located at an active plate boundary and prone to earthquake hazards. To evaluate the island’s seismic risk, the Taiwan Earthquake Model (TEM) project, supported by the Ministry of Sciences and Technology, evaluates earthquake hazard, risk, and related social and economic impact models for Taiwan through multidisciplinary collaboration. One of the major tasks of TEM is to construct a complete and updated seismogenic structure database for Taiwan to assess future seismic hazards. Toward this end, we have combined information from pre-existing databases and data obtained from new analyses to build an updated and digitized three-dimensional seismogenic structure map for Taiwan. Thirty-eight on-land active seismogenic structures are identified. For detailed information of individual structures such as their long-term slip rates and potential recurrence intervals, we collected data from existing publications, as well as calculated from results of our own field surveys and investigations. We hope this updated database would become a significant constraint for seismic hazard assessment calculations in Taiwan, and would provide important information for engineers and hazard mitigation agencies

Granger causal connectivity dissociates navigation networks that subserve allocentric and egocentric path integration

Studies on spatial navigation demonstrate a significant role of the retrosplenial complex (RSC) in the transformation of egocentric and allocentric information into complementary spatial reference frames (SRFs). The tight anatomical connections of the RSC with a wide range of other cortical regions processing spatial information support its vital role within the human navigation network. To better understand how different areas of the navigational network interact, we investigated the dynamic causal interactions of brain regions involved in solving a virtual navigation task. EEG signals were decomposed by independent component analysis (ICA) and subsequently examined for information flow between clusters of independent components (ICs) using direct short-time directed transfer function (sdDTF). The results revealed information flow between the anterior cingulate cortex and the left prefrontal cortex in the theta (4-7 Hz) frequency band and between the prefrontal, motor, parietal, and occipital cortices as well as the RSC in the alpha (8-13 Hz) frequency band. When participants prefered to use distinct reference frames (egocentric vs. allocentric) during navigation was considered, a dominant occipito-parieto-RSC network was identified in allocentric navigators. These results are in line with the assumption that the RSC, parietal, and occipital cortices are involved in transforming egocentric visual-spatial information into an allocentric reference frame. Moreover, the RSC demonstrated the strongest causal flow during changes in orientation, suggesting that this structure directly provides information on heading changes in humans

Urinary Macrophage Migration Inhibitory Factor Serves as a Potential Biomarker for Acute Kidney Injury in Patients with Acute Pyelonephritis

Conventional markers of kidney function that are familiar to clinicians, including the serum creatinine and blood urea nitrogen levels, are unable to reveal genuine injury to the kidney, and their use may delay treatment. Macrophage migration inhibitory factor (MIF) is a proinflammatory cytokine, and the predictive role and pathogenic mechanism of MIF deregulation during kidney infections involving acute kidney injury (AKI) are not currently known. In this study, we showed that elevated urinary MIF levels accompanied the development of AKI during kidney infection in patients with acute pyelonephritis (APN). In addition to the MIF level, the urinary levels of interleukin (IL)-1β and kidney injury molecule (KIM)-1 were also upregulated and were positively correlated with the levels of urinary MIF. An elevated urinary MIF level, along with elevated IL-1β and KIM-1 levels, is speculated to be a potential biomarker for the presence of AKI in APN patients

Hubba: hub objects analyzer—a framework of interactome hubs identification for network biology

One major task in the post-genome era is to reconstruct proteomic and genomic interacting networks using high-throughput experiment data. To identify essential nodes/hubs in these interactomes is a way to decipher the critical keys inside biochemical pathways or complex networks. These essential nodes/hubs may serve as potential drug-targets for developing novel therapy of human diseases, such as cancer or infectious disease caused by emerging pathogens. Hub Objects Analyzer (Hubba) is a web-based service for exploring important nodes in an interactome network generated from specific small- or large-scale experimental methods based on graph theory. Two characteristic analysis algorithms, Maximum Neighborhood Component (MNC) and Density of Maximum Neighborhood Component (DMNC) are developed for exploring and identifying hubs/essential nodes from interactome networks. Users can submit their own interaction data in PSI format (Proteomics Standards Initiative, version 2.5 and 1.0), tab format and tab with weight values. User will get an email notification of the calculation complete in minutes or hours, depending on the size of submitted dataset. Hubba result includes a rank given by a composite index, a manifest graph of network to show the relationship amid these hubs, and links for retrieving output files. This proposed method (DMNC || MNC) can be applied to discover some unrecognized hubs from previous dataset. For example, most of the Hubba high-ranked hubs (80% in top 10 hub list, and >70% in top 40 hub list) from the yeast protein interactome data (Y2H experiment) are reported as essential proteins. Since the analysis methods of Hubba are based on topology, it can also be used on other kinds of networks to explore the essential nodes, like networks in yeast, rat, mouse and human. The website of Hubba is freely available at http://hub.iis.sinica.edu.tw/Hubba