Correlation between fracture surface morphology and toughness in Zr-based bulk metallic glasses

Fracture surfaces of Zr-based bulk metallic glasses of various compositions tested in the as-cast and annealed conditions were analyzed using scanning electron microscopy. The tougher samples have shown highly jagged patterns at the beginning stage of crack propagation, and the length and roughness of this jagged pattern correlate well with the measured fracture toughness values. These jagged patterns, the main source of energy dissipation in the sample, are attributed to the formation of shear bands inside the sample. This observation provides strong evidence of significant “plastic zone” screening at the crack tip

Benefit Assessment of the Integrated Demand Management Concept for Multiple New York Metroplex Airports

Benefits of the Integrated Demand Management (IDM) concept were assessed utilizing a newly developed automated simulation capability called Traffic Management Initiative Automated Simulation (TMIAutoSim). The IDM concept focuses on improving traffic flow management (TFM) by coordinating the FAAs strategic Traffic Flow Management System (TFMS) with its more tactical Time-Based Flow Management (TBFM) system. The IDM concept leverages a new TFMS capability called Collaborative Trajectory Options Program (CTOP) to strategically pre-condition traffic demand flowing into a TBFM-managed arrival environment, where TBFM is responsible for tactically managing traffic by generating precise arrival schedules. The IDM concept was developed over a multi-year effort, focusing on solving New York metroplex airport arrival problems. TMIAutoSim closely mimics NASAs high-fidelity simulation capabilities while enabling more data to be collected at higher speed. Using this new capability, the IDM concept was evaluated using realistic traffic across various weather scenarios. Six representative weather days were selected after clustering three months of historical data. For those selected six days, Newark Liberty International Airport (EWR) and LaGuardia Airport (LGA) arrival traffic scenarios were developed. For each selected day, the historical data were analyzed to accurately simulate actual operations and the weather impact of the day. The current day operations and the IDM concept operations were simulated for the same weather scenarios and the results were compared. The selected six days were categorized into two groups: clear weather for days without Ground Delay Programs (GDP) and convective weather for days with GDP and significant weather around New York metroplex airports. For the clear weather scenarios, IDM operations reduced last minute, unanticipated departure delays for short-haul flights within TBFM control boundaries with minimal to no impact on throughput and total delay. For the convective weather scenarios, IDM significantly reduced delays and increased throughput to the destination airports

Shortlisting the influential members of criminal organizations and identifying their important communication channels

Low-level criminals, who do the legwork in a criminal organization are the most likely to be arrested, whereas the high-level ones tend to avoid attention. But crippling the work of a criminal organizations is not possible unless investigators can identify the most influential, high-level members and monitor their communication channels. Investigators often approach this task by requesting the mobile phone service records of the arrested low-level criminals to identify contacts, and then they build a network model of the organization where each node denotes a criminal and the edges represent communications. Network analysis can be used to infer the most influential criminals and most important communication channels within the network but screening all the nodes and links in a network is laborious and time consuming. Here we propose a new forensic analysis system called IICCC (Identifying Influential Criminals and their Communication Channels) that can effectively and efficiently infer the high-level criminals and short-list the important communication channels in a criminal organization, based on the mobile phone communications of its members. IICCC can also be used to build a network from crime incident reports. We evaluated IICCC experimentally and compared it with five other systems, confirming its superior prediction performance

Censor-based cooperative Multi-Antenna Spectrum Sensing with Imperfect Reporting Channels

The present contribution proposes a spectrally efficient censor-based cooperative spectrum sensing (C-CSS) approach in a sustainable cognitive radio network that consists of multiple antenna nodes and experiences imperfect sensing and reporting channels. In this context, exact analytic expressions are first derived for the corre- sponding probability of detection, probability of false alarm and sec- ondary throughput, assuming that each secondary user (SU) sends its detection outcome to a fusion center only when it has detected a primary signal. Capitalizing on the findings of the analysis, the effects of critical measures, such as the detection threshold, the number of SUs and the number of employed antennas, on the overall system performance are also quantified. In addition, the optimal detection threshold for each antenna based on the Neyman-Pearson criterion is derived and useful insights are developed on how to maximize the system throughput with a reduced number of SUs. It is shown that the C-CSS approach provides two distinct benefits compared with the conventional sensing approach, i.e., without censoring: i) the sensing tail problem, which exists in imperfect sensing environments, can be mitigated; ii) less SUs are ultimately required to obtain higher secondary throughput, rendering the system more sustainable

Predicting Phenotypic Diversity and the Underlying Quantitative Molecular Transitions

During development, signaling networks control the formation of multicellular patterns. To what extent quantitative fluctuations in these complex networks may affect multicellular phenotype remains unclear. Here, we describe a computational approach to predict and analyze the phenotypic diversity that is accessible to a developmental signaling network. Applying this framework to vulval development in C. elegans, we demonstrate that quantitative changes in the regulatory network can render ~500 multicellular phenotypes. This phenotypic capacity is an order-of-magnitude below the theoretical upper limit for this system but yet is large enough to demonstrate that the system is not restricted to a select few outcomes. Using metrics to gauge the robustness of these phenotypes to parameter perturbations, we identify a select subset of novel phenotypes that are the most promising for experimental validation. In addition, our model calculations provide a layout of these phenotypes in network parameter space. Analyzing this landscape of multicellular phenotypes yielded two significant insights. First, we show that experimentally well-established mutant phenotypes may be rendered using non-canonical network perturbations. Second, we show that the predicted multicellular patterns include not only those observed in C. elegans, but also those occurring exclusively in other species of the Caenorhabditis genus. This result demonstrates that quantitative diversification of a common regulatory network is indeed demonstrably sufficient to generate the phenotypic differences observed across three major species within the Caenorhabditis genus. Using our computational framework, we systematically identify the quantitative changes that may have occurred in the regulatory network during the evolution of these species. Our model predictions show that significant phenotypic diversity may be sampled through quantitative variations in the regulatory network without overhauling the core network architecture. Furthermore, by comparing the predicted landscape of phenotypes to multicellular patterns that have been experimentally observed across multiple species, we systematically trace the quantitative regulatory changes that may have occurred during the evolution of the Caenorhabditis genus

Development of a PbWO4 Detector for Single-Shot Positron Annihilation Lifetime Spectroscopy at the GBAR Experiment

We have developed a PbWO4 (PWO) detector with a large dynamic range to measure the intensity of a positron beam and the absolute density of the ortho-positronium (o-Ps) cloud it creates. A simulation study shows that a setup based on such detectors may be used to determine the angular distribution of the emission and reflection of o-Ps to reduce part of the uncertainties of the measurement. These will allow to improve the precision in the measurement of the cross-section for the (anti)hydrogen formation by (anti)proton-positronium charge exchange and to optimize the yield of antihydrogen ion which is an essential parameter in the GBAR experiment

Popularity-based video caching techniques for cache-enabled networks: a survey

The proliferation of the mobile Internet and connected devices, which offer a variety of services at different levels of performance is a major challenge for the fifth generation of wireless networks and beyond. Innovative solutions are needed to leverage recent advances in machine storage/memory, context awareness, and edge computing. Cache-enabled networks and techniques such as edge caching are envisioned to reduce content delivery times and traffic congestion in wireless networks. Only a few contents are popular, accounting for the majority of viewers, so caching them reduces the latency and download time. However, given the dynamic nature of user behavior, the integration of popularity prediction into caching is of paramount importance to better network utilization and user satisfaction. In this paper, we first present an overview of caching in wireless networks and then provide a detailed comparison of traditional and popularity-based caching. We discuss the attributes of videos and the evaluation criteria of caching policies. We summarize some of the recent work on proactive caching, focusing on prediction strategies. Finally, we provide insight into the potential opportunities and challenges as well as some open research problems enable the realization of efficient deployment of popularity-based caching as part of the next-generation mobile networks

Scanned Potential Microscopy of Edge and Bulk Currents in the Quantum Hall Regime

Using an atomic force microscope as a local voltmeter, we measure the Hall voltage profile in a 2D electron gas in the quantum Hall (QH) regime. We observe a linear profile in the bulk of the sample in the transition regions between QH plateaus and a distinctly nonlinear profile on the plateaus. In addition, localized voltage drops are observed at the sample edges in the transition regions. We interpret these results in terms of theories of edge and bulk currents in the QH regime.Comment: 4 pages, 5 figure

Biofabrication : reappraising the definition of an evolving field

Biofabrication is an evolving research field that has recently received significant attention. In particular, the adoption of Biofabrication concepts within the field of Tissue Engineering and Regenerative Medicine has grown tremendously, and has been accompanied by a growing inconsistency in terminology. This article aims at clarifying the position of Biofabrication as a research field with a special focus on its relation to and application for Tissue Engineering and Regenerative Medicine. Within this context, we propose a refined working definition of Biofabrication, including Bioprinting and Bioassembly as complementary strategies within Biofabrication