Nuclear structure studies of short-lived neutron-rich nuclei with the novel large-scale isochronous mass spectrometry at the FRS-ESR facility

2008 ◽  
Vol 812 (1-4) ◽  
pp. 1-12 ◽  
Author(s):  
B. Sun ◽  
R. Knöbel ◽  
Yu.A. Litvinov ◽  
H. Geissel ◽  
J. Meng ◽  
...  
Keyword(s):  
Mass Spectrometry ◽  
Nuclear Structure ◽  
Large Scale ◽  
The Novel ◽  
Isochronous Mass Spectrometry

LARGE-SCALE MASS MEASUREMENTS OF SHORT-LIVED NUCLIDES WITH THE ISOCHRONOUS MASS SPECTROMETRY AT GSI

2009 ◽  
Vol 18 (02) ◽  
pp. 346-351 ◽  
Author(s):  
B. SUN ◽  
R. KNÖBEL ◽  
YU. A. LITVINOV ◽  
S. NAKAJIMA ◽  
H. GEISSEL ◽  
...  
Keyword(s):  
Mass Spectrometry ◽  
Nuclear Structure ◽  
Large Scale ◽  
Penning Trap ◽  
Atomic Mass ◽  
Nuclear Mass ◽  
Mass Measurements ◽  
Isochronous Mass Spectrometry ◽  
R Process ◽  
Measured Mass

Precise mass measurements of short-lived exotic nuclei are very important for the understanding of basic nuclear structure physics and astrophysical nucleosynthesis in nature, as well as for the test and the development of theoretical nuclear mass models. At GSI, the Isochronous Mass Spectrometry (IMS) dedicated to mass measurements of short-lived nuclides was developed. In this contribution, the IMS technique is briefly reviewed. Recently, the first large-scale measurement on the 238 U fission fragment was done successfully. The measured mass values are in excellent agreement with the recent Penning trap data, however, they show a systematical deviation from the values in the latest atomic mass evaluation. Some representative results from this experiment will be presented, including their impact on nuclear structure physics and astrophysical r-process nucleosynthesis.

Covalent Atomic Bridges Enable Unidirectional Enhancement of Electronic Transport in Aligned Carbon Nanotubes

2019 ◽  
Author(s):  
Mingguang Chen ◽  
Wangxiang Li ◽  
Anshuman Kumar ◽  
Guanghui Li ◽  
Mikhail Itkis ◽  
...  
Keyword(s):  
Carbon Nanotubes ◽  
Electrical Transport ◽  
Large Scale ◽  
The Novel ◽  
Electrical Measurements ◽  
Metal Atoms ◽  
Aligned Carbon Nanotubes ◽  
Transport Channels ◽  
Walled Carbon Nanotubes ◽  
Bulk Structures

<p>Interconnecting the surfaces of nanomaterials without compromising their outstanding mechanical, thermal, and electronic properties is critical in the design of advanced bulk structures that still preserve the novel properties of their nanoscale constituents. As such, bridging the p-conjugated carbon surfaces of single-walled carbon nanotubes (SWNTs) has special implications in next-generation electronics. This study presents a rational path towards improvement of the electrical transport in aligned semiconducting SWNT films by deposition of metal atoms. The formation of conducting Cr-mediated pathways between the parallel SWNTs increases the transverse (intertube) conductance, while having negligible effect on the parallel (intratube) transport. In contrast, doping with Li has a predominant effect on the intratube electrical transport of aligned SWNT films. Large-scale first-principles calculations of electrical transport on aligned SWNTs show good agreement with the experimental electrical measurements and provide insight into the changes that different metal atoms exert on the density of states near the Fermi level of the SWNTs and the formation of transport channels. </p>

Algorithm of combining chromatography mass spectrometry-untargeted profiling and multivariate analysis for identification of marker-substances in samples of complex composition

2020 ◽  
Vol 86 (7) ◽  
pp. 12-19
Author(s):  
I. V. Plyushchenko ◽  
D. G. Shakhmatov ◽  
I. A. Rodin
Keyword(s):  
Mass Spectrometry ◽  
Multivariate Analysis ◽  
Large Scale ◽  
Complex Composition ◽  
Unified Protocol ◽  
Chromatography Mass Spectrometry ◽  
Marker Substances ◽  
Selection Testing ◽  
Untargeted Profiling

A viral development of statistical data processing, computing capabilities, chromatography-mass spectrometry, and omics technologies (technologies based on the achievements of genomics, transcriptomics, proteomics, metabolomics) in recent decades has not led to formation of a unified protocol for untargeted profiling. Systematic errors reduce the reproducibility and reliability of the obtained results, and at the same time hinder consolidation and analysis of data gained in large-scale multi-day experiments. We propose an algorithm for conducting omics profiling to identify potential markers in the samples of complex composition and present the case study of urine samples obtained from different clinical groups of patients. Profiling was carried out by the method of liquid chromatography mass spectrometry. The markers were selected using methods of multivariate analysis including machine learning and feature selection. Testing of the approach was performed using an independent dataset by clustering and projection on principal components.

scholarly journals IoT Traffic: Modeling and Measurement Experiments

IoT ◽  
2021 ◽  
Vol 2 (1) ◽  
pp. 140-162
Author(s):  
Hung Nguyen-An ◽  
Thomas Silverston ◽  
Taku Yamazaki ◽  
Takumi Miyoshi
Keyword(s):  
Smart Home ◽  
Large Scale ◽  
Traffic Modeling ◽  
The Novel ◽  
Network Behavior ◽  
Performance Accuracy ◽  
Traffic Generator ◽  
Multiple Devices ◽  
Iot Devices ◽  
The Internet Of Things

We now use the Internet of things (IoT) in our everyday lives. The novel IoT devices collect cyber–physical data and provide information on the environment. Hence, IoT traffic will count for a major part of Internet traffic; however, its impact on the network is still widely unknown. IoT devices are prone to cyberattacks because of constrained resources or misconfigurations. It is essential to characterize IoT traffic and identify each device to monitor the IoT network and discriminate among legitimate and anomalous IoT traffic. In this study, we deployed a smart-home testbed comprising several IoT devices to study IoT traffic. We performed extensive measurement experiments using a novel IoT traffic generator tool called IoTTGen. This tool can generate traffic from multiple devices, emulating large-scale scenarios with different devices under different network conditions. We analyzed the IoT traffic properties by computing the entropy value of traffic parameters and visually observing the traffic on behavior shape graphs. We propose a new method for identifying traffic entropy-based devices, computing the entropy values of traffic features. The method relies on machine learning to classify the traffic. The proposed method succeeded in identifying devices with a performance accuracy up to 94% and is robust with unpredictable network behavior with traffic anomalies spreading in the network.

scholarly journals Multi-Objective Optimization of Integrated Civilian-Military Scheduling of Medical Supplies for Epidemic Prevention and Control

Healthcare ◽  
2021 ◽  
Vol 9 (2) ◽  
pp. 126
Author(s):  
Hai-Feng Ling ◽  
Zheng-Lian Su ◽  
Xun-Lin Jiang ◽  
Yu-Jun Zheng
Keyword(s):  
Prevention And Control ◽  
Large Scale ◽  
Medical Services ◽  
The Novel ◽  
Multi Objective ◽  
Medical Supplies ◽  
Problem Instances ◽  
Novel Coronavirus ◽  
And Control ◽  
Minimum Ratio

In a large-scale epidemic, such as the novel coronavirus pneumonia (COVID-19), there is huge demand for a variety of medical supplies, such as medical masks, ventilators, and sickbeds. Resources from civilian medical services are often not sufficient for fully satisfying all of these demands. Resources from military medical services, which are normally reserved for military use, can be an effective supplement to these demands. In this paper, we formulate a problem of integrated civilian-military scheduling of medical supplies for epidemic prevention and control, the aim of which is to simultaneously maximize the overall satisfaction rate of the medical supplies and minimize the total scheduling cost, while keeping a minimum ratio of medical supplies reservation for military use. We propose a multi-objective water wave optimization (WWO) algorithm in order to efficiently solve this problem. Computational results on a set of problem instances constructed based on real COVID-19 data demonstrate the effectiveness of the proposed method.

scholarly journals Comparative genomics suggests a taxonomic revision of the Staphylococcus cohnii species complex

2021 ◽  
Author(s):  
Anna Lavecchia ◽  
Matteo Chiara ◽  
Caterina De Virgilio ◽  
Caterina Manzari ◽  
Carlo Pazzani ◽  
...  
Keyword(s):  
Comparative Genomics ◽  
Species Complex ◽  
Large Scale ◽  
Genomic Sequence ◽  
Bacterial Species ◽  
Taxonomic Revision ◽  
Distinct Species ◽  
The Novel ◽  
Staphylococcus Cohnii ◽  
Taxonomic Assignments

Abstract Staphylococcus cohnii (SC), a coagulase-negative bacterium, was first isolated in 1975 from human skin. Early phenotypic analyses led to the delineation of two subspecies (subsp.), Staphylococcus cohnii subsp. cohnii (SCC) and Staphylococcus cohnii subsp. urealyticus (SCU). SCC was considered to be specific to humans whereas SCU apparently demonstrated a wider host range, from lower primates to humans. The type strains ATCC 29974 and ATCC 49330 have been designated for SCC and SCU, respectively. Comparative analysis of 66 complete genome sequences—including a novel SC isolate—revealed unexpected patterns within the SC complex, both in terms of genomic sequence identity and gene content, highlighting the presence of 3 phylogenetically distinct groups. Based on our observations, and on the current guidelines for taxonomic classification for bacterial species, we propose a revision of the SC species complex. We suggest that SCC and SCU should be regarded as two distinct species: SC and SU (Staphylococcus urealyticus), and that two distinct subspecies, SCC and SCB (SC subsp. barensis, represented by the novel strain isolated in Bari) should be recognized within SC. Furthermore, since large scale comparative genomics studies recurrently suggest inconsistencies or conflicts in taxonomic assignments of bacterial species, we believe that the approach proposed here might be considered for more general application.

A multi-objective sparse evolutionary framework for large-scale weapon target assignment based on a reward strategy

2021 ◽  
Vol 40 (5) ◽  
pp. 10043-10061
Author(s):  
Xiaoping Shi ◽  
Shiqi Zou ◽  
Shenmin Song ◽  
Rui Guo
Keyword(s):  
Large Scale ◽  
The Novel ◽  
Genetic Operators ◽  
Multi Objective ◽  
Target Assignment ◽  
Solution Selection ◽  
Battlefield Environment ◽  
Sparse Problems ◽  
Novel Model ◽  
Error Parameter

 The asset-based weapon target assignment (ABWTA) problem is one of the important branches of the weapon target assignment (WTA) problem. Due to the current large-scale battlefield environment, the ABWTA problem is a multi-objective optimization problem (MOP) with strong constraints, large-scale and sparse properties. The novel model of the ABWTA problem with the operation error parameter is established. An evolutionary algorithm for large-scale sparse problems (SparseEA) is introduced as the main framework for solving large-scale sparse ABWTA problem. The proposed framework (SparseEA-ABWTA) mainly addresses the issue that problem-specific initialization method and genetic operators with a reward strategy can generate solutions efficiently considering the sparsity of variables and an improved non-dominated solution selection method is presented to handle the constraints. Under the premise of constructing large-scale cases by the specific case generator, two numerical experiments on four outstanding multi-objective evolutionary algorithms (MOEAs) show Runtime of SparseEA-ABWTA is faster nearly 50% than others under the same convergence and the gap between MOEAs improved by the mechanism of SparseEA-ABWTA and SparseEA-ABWTA is reduced to nearly 20% in the convergence and distribution.

scholarly journals Automated 16-Plex Plasma Proteomics with Real-Time Search and Ion Mobility Mass Spectrometry Enables Large-Scale Profiling in Naked Mole-Rats and Mice

2021 ◽  
Vol 20 (2) ◽  
pp. 1280-1295
Author(s):  
Aleksandr Gaun ◽  
Kaitlyn N. Lewis Hardell ◽  
Niclas Olsson ◽  
Jonathon J. O’Brien ◽  
Sudha Gollapudi ◽  
...  
Keyword(s):  
Mass Spectrometry ◽  
Real Time ◽  
Ion Mobility ◽  
Large Scale ◽  
Ion Mobility Mass Spectrometry ◽  
Plasma Proteomics ◽  
Rats And Mice

Derivation of Pheromone-Based Larval Thresholds in Spruce Budworm Accounting for Distance to Defoliated Forest Stands

2021 ◽  
Author(s):  
Marc Rhainds ◽  
Ian DeMerchant ◽  
Pierre Therrien
Keyword(s):  
Boreal Forests ◽  
Large Scale ◽  
Choristoneura Fumiferana ◽  
Intervention Strategy ◽  
Spruce Budworm ◽  
Interactive Effects ◽  
The Novel ◽  
Forest Stands ◽  
General Guideline ◽  
Number Of Males

Abstract Spruce budworm, Choristoneura fumiferana Clem. (Lepidoptera: Tortricidae), is the most severe defoliator of Pinaceae in Nearctic boreal forests. Three tools widely used to guide large-scale management decisions (year-to-year defoliation maps; density of overwintering second instars [L2]; number of males at pheromone traps) were integrated to derive pheromone-based thresholds corresponding to specific intergenerational transitions in larval densities (L2i → L2i+1), taking into account the novel finding that threshold estimates decline with distance to defoliated forest stands (DIST). Estimates of thresholds were highly variable between years, both numerically and in terms of interactive effects of L2i and DIST, which limit their heuristic value. In the context of early intervention strategy (L2i+1 &gt; 6.5 individuals per branch), however, thresholds fluctuated within relatively narrow intervals across wide ranges of L2i and DIST, and values of 40–200 males per trap may thus be used as general guideline.

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