On AIPS++, a new astronomical information processing system

The AIPS system that has served the needs of the radio astronomical community remarkably well during the last 15 years is showing signs of age and is being replaced by a more modern system, AIPS++. As the name implies, AIPS++ will be developed in a object oriented fashion and will use C++ as its main programming language. The work is being done by a consortium of seven organizations, with coordinated activities worldwide. After a review of the history of the project to this date from management, astronomical and technical viewpoints, and the current state of the project, the paper concentrates on the tradeoffs implied by the choice of implementation style and the lessons we have learned, good and bad

Mean Field Renormalization Group for the Boundary Magnetization of Strip Clusters

We analyze in some detail a recently proposed transfer matrix mean field approximation which yields the exact critical point for several two dimensional nearest neighbor Ising models. For the square lattice model we show explicitly that this approximation yields not only the exact critical point, but also the exact boundary magnetization of a semi--infinite Ising model, independent of the size of the strips used. Then we develop a new mean field renormalization group strategy based on this approximation and make connections with finite size scaling. Applying our strategy to the quadratic Ising and three--state Potts models we obtain results for the critical exponents which are in excellent agreement with the exact ones. In this way we also clarify some advantages and limitations of the mean field renormalization group approach.Comment: 16 pages (plain TeX) + 8 figures (PostScript, appended), POLFIS-TH.XX/9

Case report on postmortem fentanyl measurement after overdose with more than 67 fentanyl patches

PURPOSE: Fentanyl is an analgesic that is frequently prescribed, which resulted in non-intentional as well as intentional misuse and deaths. Here, we present a postmortem case of a patient who clearly died of a fentanyl overdose due to an extensive number of fentanyl patches combined with oral intake of fentanyl and cocaine. We aimed to show how postmortem analysis can be used to interpret postmortem fentanyl concentrations in unique cases like the one we present. CASE DESCRIPTION: A 23-year-old male was found dead in his bedroom with 67 non-prescribed patches of fentanyl on his body. In the room, there also were fentanyl tablets of 100 µg and cocaine powder, which had possibly also been taken by the deceased. To confirm the cause of death, urine and subclavian blood were retrieved to perform a standard postmortem toxicology screening. The toxicological screening revealed the presence of several drugs, including cocaine, fentanyl, lidocaine and paracetamol. Further analysis of the quantitative postmortem values of fentanyl with ultra-performance liquid chromatography-tandem mass spectrometry revealed a fentanyl concentration of 57.9 µg/L. Considering several issues around postmortem drug analyses, this value seemed to be in line with concentrations found in previously reported postmortem cases. CONCLUSION: We were able to confirm the expected cause of death with an extensive toxicological screening in combination with the circumstantial evidence. We identified fentanyl as most important cause for the fatal outcome in this specific case and simultaneously contributed to the limited availability of knowledge on postmortem fentanyl concentrations

SOT-MRAM 300mm integration for low power and ultrafast embedded memories

We demonstrate for the first time full-scale integration of top-pinned perpendicular MTJ on 300 mm wafer using CMOS-compatible processes for spin-orbit torque (SOT)-MRAM architectures. We show that 62 nm devices with a W-based SOT underlayer have very large endurance (> 5x10^10), sub-ns switching time of 210 ps, and operate with power as low as 300 pJ.Comment: presented at VLSI2018 session C8-

NeAT: a toolbox for the analysis of biological networks, clusters, classes and pathways

The network analysis tools (NeAT) (http://rsat.ulb.ac.be/neat/) provide a user-friendly web access to a collection of modular tools for the analysis of networks (graphs) and clusters (e.g. microarray clusters, functional classes, etc.). A first set of tools supports basic operations on graphs (comparison between two graphs, neighborhood of a set of input nodes, path finding and graph randomization). Another set of programs makes the connection between networks and clusters (graph-based clustering, cliques discovery and mapping of clusters onto a network). The toolbox also includes programs for detecting significant intersections between clusters/classes (e.g. clusters of co-expression versus functional classes of genes). NeAT are designed to cope with large datasets and provide a flexible toolbox for analyzing biological networks stored in various databases (protein interactions, regulation and metabolism) or obtained from high-throughput experiments (two-hybrid, mass-spectrometry and microarrays). The web interface interconnects the programs in predefined analysis flows, enabling to address a series of questions about networks of interest. Each tool can also be used separately by entering custom data for a specific analysis. NeAT can also be used as web services (SOAP/WSDL interface), in order to design programmatic workflows and integrate them with other available resources

Seroprevalence of HIV, hepatitis b, and hepatitis c among opioid drug users on methadone treatment in the netherlands

Background: Injecting drug users (IDU) remain an important population at risk for blood-borne infections such as human immunodeficiency virus (HIV), hepatitis B virus (HBV) and hepatitis C virus (HCV). In the Netherlands, a program is being implemented to offer annual voluntary screening for these infections to opioid drug users (ODUs) screened in methadone care. At two care sites where the program is now operating, our study aimed to estimate the seroprevalence among ODUs screened for HIV, HBV and HCV; to evaluate HBV vaccination coverage; and to assess the feasibility of monitoring seroprevalence trends by using routine annual screening data.Methods: Opioid drug users on methadone treatment are routinely offered voluntary screening for infectious diseases such as HIV, HBV and HCV. Data on uptake and outcome of anti-HIV, anti-HBc, and anti-HCV screening among ODUs receiving methadone were obtained from two regions: Amsterdam from 2004 to 2008 and Heerlen from 2003 to 2009.Findings: Annual screening uptake for HIV, HBV and HCV varied from 34 to 69%, depending on disease and screening site. Of users screened, 2.5% were HIV-positive in Amsterdam and 11% in Heerlen; 26% were HCV-positive in Amsterdam and 61% in Heerlen. Of those screened for HBV, evidence of current or previous infection (anti-HBc) was found among 33% in Amsterdam and 48% in Heerlen. In Amsterdam, 92% were fully vaccinated for HBV versus 45% in Heerlen.Conclusion: Annual screening for infectious diseases in all ODUs in methadone care is not fully implemented in the Netherlands. On average, more than half of the ODUs in methadone care in Heerlen and Amsterdam were screened for HIV, HBV and HCV. In addition, screening data indicate that HBV vaccination uptake was rather high. While the HIV prevalence among these ODUs was relatively low compared to other drug-using populations, the high HCV prevalence among this group underscores the need to expand annual screening and interventions to monitor HIV, HBV and HCV in the opioid drug-using population

NeAT: a toolbox for the analysis of biological networks, clusters, classes and pathways

The network analysis tools (NeAT) (http://rsat.ulb.ac.be/neat/) provide a user-friendly web access to a collection of modular tools for the analysis of networks (graphs) and clusters (e.g. microarray clusters, functional classes, etc.). A first set of tools supports basic operations on graphs (comparison between two graphs, neighborhood of a set of input nodes, path finding and graph randomization). Another set of programs makes the connection between networks and clusters (graph-based clustering, cliques discovery and mapping of clusters onto a network). The toolbox also includes programs for detecting significant intersections between clusters/classes (e.g. clusters of co-expression versus functional classes of genes). NeAT are designed to cope with large datasets and provide a flexible toolbox for analyzing biological networks stored in various databases (protein interactions, regulation and metabolism) or obtained from high-throughput experiments (two-hybrid, mass-spectrometry and microarrays). The web interface interconnects the programs in predefined analysis flows, enabling to address a series of questions about networks of interest. Each tool can also be used separately by entering custom data for a specific analysis. NeAT can also be used as web services (SOAP/WSDL interface), in order to design programmatic workflows and integrate them with other available resources

Multi-interaction mean-field renormalization group

We present an extension of the previously proposed mean-field renormalization method to model Hamiltonians which are characterized by more than just one type of interaction. The method rests on scaling assumptions about the magnetization of different sublattices of the given lattice and it generates as many flow equations as coupling constants without arbitrary truncations on the renormalized Hamiltonian. We obtain good results for the test case of Ising systems with an additional second-neighbor coupling in two and three dimensions. An application of the method is also done to a morphological model of interacting surfaces introduced recenlty by Likos, Mecke and Wagner [J. Chem. Phys. {\bf{102}}, 9350 (1995)]. PACS: 64.60.Ak, 64.60.Fr, 05.70.JkComment: Tex file and three macros appended at the end. Five figures available upon request to: [email protected], Fax: [+]39-40-224-60

The status of cheetah and African wild dog in the Benoue Ecosystem, North Cameroon

Conservation Biology - ol