Synthesis and characterization of Fe3O4@Cs@Ag nanocomposite and its use in the production of magnetic and antibacterial nanofibrous membranes

Electrospinning is a promising technique to produce polymeric as well as metal oxide nanofibers in diverse domains. In this work, different weight ratios (5%, 7.5% and 10%) of Fe3O4@Cs@Ag magnetic nanoparticles were added in PVP (polyvinylpyrrolidone) polymer and fabricated via electrospinning method to produce magnetic nanofibers (MNFs). Structural, magnetic, morphological, spectroscopic and thermal properties of produced nanofibers were characterized. Furtheremore, antibacterial effects of Fe3O4@Cs@Ag nanofibrous membrane was investigated. Obtained SEM images showed that produced nanofibers were uniform and defect free. Moreover, crystallinity and magnetic moment of fibers was tested by using X-ray diffraction and a vibrating sample magnetometer. The results showed that produced nanofibrous membranes exhibited good antibacterial activity versus Staphylococcus aureus, Bacillus subtilis, Enterococcus faecalis, Escherichia coli, Proteus mirabilis and Pseudomonas aeruginosa. © 2020National Science Foundation, NSF; Directorate for Mathematical and Physical Sciences, MPS: 1726617This work was supported in part by Scientific Research Unit of Nam?k Kemal University within NKUBAP.06.GA.19.195 coded project. Magnetic Characterization at Virginia Commonwealth University was partially supported by National Science Foundation, Award Number: 1726617.This work was supported in part by Scientific Research Unit of Namık Kemal University within NKUBAP.06.GA.19.195 coded project. Magnetic Characterization at Virginia Commonwealth University was partially supported by National Science Foundation , Award Number: 1726617

CMDX©-based single source information system for simplified quality management and clinical research in prostate cancer

Background: Histopathological evaluation of prostatectomy specimens is crucial to decision-making and prediction of patient outcomes in prostate cancer (PCa). Topographical information regarding PCa extension and positive surgical margins (PSM) is essential for clinical routines, quality assessment, and research. However, local hospital information systems (HIS) often do not support the documentation of such information. Therefore, we investigated the feasibility of integrating a cMDX-based pathology report including topographical information into the clinical routine with the aims of obtaining data, performing analysis and generating heat maps in a timely manner, while avoiding data redundancy. Methods: We analyzed the workflow of the histopathological evaluation documentation process. We then developed a concept for a pathology report based on a cMDX data model facilitating the topographical documentation of PCa and PSM; the cMDX SSIS is implemented within the HIS of University Hospital Muenster. We then generated a heat map of PCa extension and PSM using the data. Data quality was assessed by measuring the data completeness of reports for all cases, as well as the source-to-database error. We also conducted a prospective study to compare our proposed method with recent retrospective and paper-based studies according to the time required for data analysis. Results: We identified 30 input fields that were applied to the cMDX-based data model and the electronic report was integrated into the clinical workflow. Between 2010 and 2011, a total of 259 reports were generated with 100% data completeness and a source-to-database error of 10.3 per 10,000 fields. These reports were directly reused for data analysis, and a heat map based on the data was generated. PCa was mostly localized in the peripheral zone of the prostate. The mean relative tumor volume was 16.6%. The most PSM were localized in the apical region of the prostate. In the retrospective study, 1623 paper-based reports were transferred to cMDX reports; this process took 15 ± 2 minutes per report. In a paper-based study, the analysis data preparation required 45 ± 5 minutes per report. Conclusions: cMDX SSIS can be integrated into the local HIS and provides clinical routine data and timely heat maps for quality assessment and research purposes.

Collaborative Broadcast in O(log log n) Rounds

We consider the multihop broadcasting problem for $n$ nodes placed uniformly at random in a disk and investigate the number of hops required to transmit a signal from the central node to all other nodes under three communication models: Unit-Disk-Graph (UDG), Signal-to-Noise-Ratio (SNR), and the wave superposition model of multiple input/multiple output (MIMO). In the MIMO model, informed nodes cooperate to produce a stronger superposed signal. We do not consider the problem of transmitting a full message nor do we consider interference. In each round, the informed senders try to deliver to other nodes the required signal strength such that the received signal can be distinguished from the noise. We assume sufficiently high node density $\rho= \Omega(\log n)$. In the unit-disk graph model, broadcasting needs $O(\sqrt{n/\rho})$ rounds. In the other models, we use an Expanding Disk Broadcasting Algorithm, where in a round only triggered nodes within a certain distance from the initiator node contribute to the broadcasting operation. This algorithm achieves a broadcast in only $O(\frac{\log n}{\log \rho})$ rounds in the SNR-model. Adapted to the MIMO model, it broadcasts within $O(\log \log n - \log \log \rho)$ rounds. All bounds are asymptotically tight and hold with high probability, i.e. $1- n^{-O(1)}$.Comment: extended abstract accepted for ALGOSENSORS 201

A four-dimensional {\Lambda}CDM-type cosmological model induced from higher dimensions using a kinematical constraint

A class of cosmological solutions of higher dimensional Einstein field equations with the energy-momentum tensor of a homogeneous, isotropic fluid as the source are considered with an anisotropic metric that includes the direct sum of a 3-dimensional (physical, flat) external space metric and an n-dimensional (compact, flat) internal space metric. A simple kinematical constraint is postulated that correlates the expansion rates of the external and internal spaces in terms of a real parameter {\lambda}. A specific solution for which both the external and internal spaces expand at different rates is given analytically for n=3. Assuming that the internal dimensions were at Planck length scales when the external space starts with a Big Bang (t=0), they expand only 1.49 times and stay at Planck length scales even in the present age of the universe (13.7 Gyr). The effective four dimensional universe would exhibit a behavior consistent with our current understanding of the observed universe. It would start in a stiff fluid dominated phase and evolve through radiation dominated and pressureless matter dominated phases, eventually going into a de Sitter phase at late times.Comment: 12 pages, 8 figures; matches the version published in General Relativity and Gravitatio

Experimental Assessment of Linear Sampling and Factorization Methods for Microwave Imaging of Concealed Targets

Shape reconstruction methods are particularly well suited for imaging of concealed targets. Yet, these methods are rarely employed in real nondestructive testing applications, since they generally require the electrical parameters of outer object as a priori knowledge. In this regard, we propose an approach to relieve two well known shape reconstruction algorithms, which are the linear sampling and the factorization methods, from the requirement of the a priori knowledge on electrical parameters of the surrounding medium. The idea behind this paper is that if a measurement of the reference medium (a medium which can approximate the material, except the inclusion) can be supplied to these methods, reconstructions with very high qualities can be obtained even when there is no information about the electrical parameters of the surrounding medium. Taking the advantage of this idea, we consider that it is possible to use shape reconstruction methods in buried object detection. To this end, we perform several experiments inside an anechoic chamber to verify the approach against real measurements. Accuracy and stability of the obtained results show that both the linear sampling and the factorization methods can be quite useful for various buried obstacle imaging problems

Network centrality: an introduction

Centrality is a key property of complex networks that influences the behavior of dynamical processes, like synchronization and epidemic spreading, and can bring important information about the organization of complex systems, like our brain and society. There are many metrics to quantify the node centrality in networks. Here, we review the main centrality measures and discuss their main features and limitations. The influence of network centrality on epidemic spreading and synchronization is also pointed out in this chapter. Moreover, we present the application of centrality measures to understand the function of complex systems, including biological and cortical networks. Finally, we discuss some perspectives and challenges to generalize centrality measures for multilayer and temporal networks.Comment: Book Chapter in "From nonlinear dynamics to complex systems: A Mathematical modeling approach" by Springe

U-Compare bio-event meta-service: compatible BioNLP event extraction services

AbstractBackgroundBio-molecular event extraction from literature is recognized as an important task of bio text mining and, as such, many relevant systems have been developed and made available during the last decade. While such systems provide useful services individually, there is a need for a meta-service to enable comparison and ensemble of such services, offering optimal solutions for various purposes.ResultsWe have integrated nine event extraction systems in the U-Compare framework, making them inter-compatible and interoperable with other U-Compare components. The U-Compare event meta-service provides various meta-level features for comparison and ensemble of multiple event extraction systems. Experimental results show that the performance improvements achieved by the ensemble are significant. ConclusionsWhile individual event extraction systems themselves provide useful features for bio text mining, the U-Compare meta-service is expected to improve the accessibility to the individual systems, and to enable meta-level uses over multiple event extraction systems such as comparison and ensemble.This research was partially supported by KAKENHI 18002007 [YK, MM, JDK, SP, TO, JT]; JST PRESTO and KAKENHI 21500130 [YK]; the Academy of Finland and computational resources were provided by CSC -- IT Center for Science Ltd [JB, FG]; the Research Foundation Flanders (FWO) [SVL]; UK Biotechnology and Biological Sciences, Research Council (BBSRC project BB/G013160/1 Automated Biological Event Extraction from the Literature for Drug Discovery) and JISC, National Centre for Text Mining [SA]; the Spanish grant BIO2010-17527 [MN, APM]; NIH Grant U54 DA021519 [AO, DRR]Peer Reviewe

Advances and Open Problems in Federated Learning

Federated learning (FL) is a machine learning setting where many clients (e.g. mobile devices or whole organizations) collaboratively train a model under the orchestration of a central server (e.g. service provider), while keeping the training data decentralized. FL embodies the principles of focused data collection and minimization, and can mitigate many of the systemic privacy risks and costs resulting from traditional, centralized machine learning and data science approaches. Motivated by the explosive growth in FL research, this paper discusses recent advances and presents an extensive collection of open problems and challenges.Comment: Published in Foundations and Trends in Machine Learning Vol 4 Issue 1. See: https://www.nowpublishers.com/article/Details/MAL-08