scholarly journals DyTER – Dynamic Track and Event Reconstruction

2019 ◽  
Vol 214 ◽  
pp. 02026
Author(s):  
Michael Papenbrock
Keyword(s):  
Pattern Matching ◽  
Particle Track ◽  
Track Reconstruction ◽  
Proton Collisions ◽  
Panda Experiment ◽  
Event Reconstruction ◽  
Wide Range ◽  
Future Challenges ◽  
Event Rates ◽  
Specific Particle

The future PANDA experiment at FAIR experiment aims to cover a wide range of processes in antiproton-proton collisions at event rates of up to 20 MHz. Such event rates make reconstruction a challenging task for the purely software-based event filter. Investigating complex event topologies with displaced vertices increases the difficulty even further. Here we present two attempts to meet these future challenges: an algorithm for track reconstruction based on pattern matching with pre-determined look-up tables, and as a continuation of this approach a system of neural networks for identifying specific particle track candidates and predicting their momentum.

scholarly journals Track Reconstruction with PANDA at FAIR

2020 ◽  
Vol 245 ◽  
pp. 01029
Author(s):  
Michael Papenbrock ◽  
Walter Ikegami Andersson ◽  
Jenny Regina
Keyword(s):  
Spatial Information ◽  
Reconstruction Algorithms ◽  
Track Reconstruction ◽  
Proton Collisions ◽  
Panda Experiment ◽  
Straw Tube ◽  
Pattern Recognition Methods ◽  
Event Reconstruction ◽  
Wide Range ◽  
Time Stamps

The future PANDA experiment at FAIR aims to investigate a wide range of physics processes in antiproton-proton collisions at rates of up to 20 MHz, while employing a purely software-based event filter. To educate the trigger decisions, a full event reconstruction has to be carried out in real time. This challenge is amplified when considering tracks from particles with long lifetimes and displaced decay vertices, which add to the complexity of the reconstruction algorithms. Here, we present modifications to a cellular automatonbased track finder taking detector time-stamps into account in addition to spatial information, as well as several pattern recognition methods for longitudinal track reconstrucion with PANDA’s Straw Tube Tracker.

scholarly journals Electrodeposited Hydroxyapatite-Based Biocoatings: Recent Progress and Future Challenges

Coatings ◽  
2021 ◽  
Vol 11 (1) ◽  
pp. 110
Author(s):  
Mir Saman Safavi ◽  
Frank C. Walsh ◽  
Maria A. Surmeneva ◽  
Roman A. Surmenev ◽  
Jafar Khalil-Allafi
Keyword(s):  
Recent Progress ◽  
Tribological Behavior ◽  
Metallic Materials ◽  
Industrial Processing ◽  
Component Size ◽  
Polymeric Particles ◽  
Operational Variables ◽  
Wide Range ◽  
Future Challenges ◽  
Coating Methods

Hydroxyapatite has become an important coating material for bioimplants, following the introduction of synthetic HAp in the 1950s. The HAp coatings require controlled surface roughness/porosity, adequate corrosion resistance and need to show favorable tribological behavior. The deposition rate must be sufficiently fast and the coating technique needs to be applied at different scales on substrates having a diverse structure, composition, size, and shape. A detailed overview of dry and wet coating methods is given. The benefits of electrodeposition include controlled thickness and morphology, ability to coat a wide range of component size/shape and ease of industrial processing. Pulsed current and potential techniques have provided denser and more uniform coatings on different metallic materials/implants. The mechanism of HAp electrodeposition is considered and the effect of operational variables on deposit properties is highlighted. The most recent progress in the field is critically reviewed. Developments in mineral substituted and included particle, composite HAp coatings, including those reinforced by metallic, ceramic and polymeric particles; carbon nanotubes, modified graphenes, chitosan, and heparin, are considered in detail. Technical challenges which deserve further research are identified and a forward look in the field of the electrodeposited HAp coatings is taken.

scholarly journals Using chemical biology to assess and modulate mitochondria: progress and challenges

2017 ◽  
Vol 7 (2) ◽  
pp. 20160151 ◽  
Author(s):  
Angela Logan ◽  
Michael P. Murphy
Keyword(s):  
Mitochondrial Function ◽  
Chemical Biology ◽  
Biomedical Sciences ◽  
Interdisciplinary Approaches ◽  
Wide Range ◽  
Challenges And Opportunities ◽  
Future Challenges ◽  
The Many ◽  
Opening Up

Our understanding of the role of mitochondria in biomedical sciences has expanded considerably over the past decade. In addition to their well-known metabolic roles, mitochondrial are also central to signalling for various processes through the generation of signals such as ROS and metabolites that affect cellular homeostasis, as well as other processes such as cell death and inflammation. Thus, mitochondrial function and dysfunction are central to the health and fate of the cell. Consequently, there is considerable interest in better understanding and assessing the many roles of mitochondria. Furthermore, there is also a growing realization that mitochondrial are a promising drug target in a wide range of pathologies. The application of interdisciplinary approaches at the interface between chemistry and biology are opening up new opportunities to understand mitochondrial function and in assessing the role of the organelle in biology. This work and the experience thus gained are leading to the development of new classes of therapies. Here, we overview the progress that has been made to date on exploring the chemical biology of the organelle and then focus on future challenges and opportunities that face this rapidly developing field.

scholarly journals CubeSat Communications: Recent Advances and Future Challenges

2020 ◽  
Author(s):  
Nasir Saeed ◽  
Ahmed Elzanaty ◽  
Heba Almorad ◽  
Hayssam Dahrouj ◽  
Tareq Y. Al-Naffouri ◽  
...  
Keyword(s):  
Channel Modeling ◽  
Future Research ◽  
New Paradigm ◽  
Earth Remote Sensing ◽  
Research Directions ◽  
Space Industry ◽  
Recent Advances ◽  
Wide Range ◽  
Future Challenges ◽  
Future Research Directions

<pre><pre>Given the increasing number of space-related applications, research in the emerging space industry is becoming more and more attractive. One compelling area of current space research is the design of miniaturized satellites, known as CubeSats, which are enticing because of their numerous applications and low design-and-deployment cost. </pre><pre>The new paradigm of connected space through CubeSats makes possible a wide range of applications, such as Earth remote sensing, space exploration, and rural connectivity.</pre><pre>CubeSats further provide a complementary connectivity solution to the pervasive Internet of Things (IoT) networks, leading to a globally connected cyber-physical system.</pre><pre>This paper presents a holistic overview of various aspects of CubeSat missions and provides a thorough review of the topic from both academic and industrial perspectives.</pre><pre>We further present recent advances in the area of CubeSat communications, with an emphasis on constellation-and-coverage issues, channel modeling, modulation and coding, and networking.</pre><pre>Finally, we identify several future research directions for CubeSat communications, including Internet of space things, low-power long-range networks, and machine learning for CubeSat resource allocation.</pre></pre>

scholarly journals First Demonstration of a Pixelated Charge Readout for Single-Phase Liquid Argon Time Projection Chambers

Instruments ◽  
2020 ◽  
Vol 4 (1) ◽  
pp. 9 ◽  
Author(s):  
Jonathan Asaadi ◽  
Martin Auger ◽  
Antonio Ereditato ◽  
Damian Goeldi ◽  
Umut Kose ◽  
...  
Keyword(s):  
Single Phase ◽  
Signal To Noise Ratio ◽  
Liquid Argon ◽  
Track Reconstruction ◽  
3D Tracking ◽  
3D Space ◽  
Time Projection Chambers ◽  
Event Reconstruction ◽  
Phase Liquid ◽  
Time Projection

Traditional charge readout technologies of single-phase Liquid Argon Time projection Chambers (LArTPCs) based on projective wire readout introduce intrinsic ambiguities in event reconstruction. Combined with the slow response inherent in LArTPC detectors, reconstruction ambiguities have limited their performance, until now. Here, we present a proof of principle of a pixelated charge readout that enables the full 3D tracking capabilities of LArTPCs. We characterize the signal-to-noise ratio of charge readout chain to be about 14, and demonstrate track reconstruction on 3D space points produced by the pixel readout. This pixelated charge readout makes LArTPCs a viable option for high-multiplicity environments.

4302Machine-learning integration of complex echocardiographic patterns and clinical parameters from cohorts and trials

2019 ◽  
Vol 40 (Supplement_1) ◽  
Author(s):  
M Cikes ◽  
S Sanchez Martinez ◽  
B Claggett ◽  
S D Solomon ◽  
B Bijnens
Keyword(s):  
Event Rate ◽  
Dimensional Space ◽  
Myocardial Infarct ◽  
Cardiac Resynchronization ◽  
Clinical Parameters ◽  
Volume Curve ◽  
Wide Range ◽  
Deformation Properties ◽  
Event Rates ◽  
Left Figure

Abstract Introduction Contemporary machine learning (ML) allows comparing individuals based on a wide range of heterogenous data. We aimed to use similarity-based unsupervised ML to integrate clinical variables and complex imaging patterns from a population-based cohort (Atherosclerosis Risk in Communities study - ARIC) with a HFPEF (Treatment of Preserved Cardiac Function Heart Failure with an Aldosterone Antagonist - TOPCAT) as well as a HFREF (Multicenter Automatic Defibrillator Implantation Trial with Cardiac Resynchronization Therapy - MADIT-CRT) clinical trial and to predict the outcome of the patients based on their location in the derived ML universe, rather than on their original cohort. Methods An unsupervised ML for dimensionality reduction algorithm (multiple kernel learning) was trained using 2123 subjects enrolled in ARIC. The algorithm positioned them based on similarities in longitudinal strain patterns of 12 LV regions and an LV volume curve, together with 17 clinical parameters (age, sex, myocardial infarct, QRS width, prior HF, LVEDVi, LAVi, race, heart rate, SBP, BP meds, diabetes, smoking status, BMI, GLS, LVMi, LVEF). Using the same descriptors, 105 untreated TOPCAT and 429 untreated MADIT-CRT patients were projected onto the learned space (upper-left figure). A k-means algorithm was subsequently used to partition the resulting space into 3 clusters (broadly speaking, the number of expected clinical categories: controls (ARIC), HFPEFs (TOPCAT) and HFREFs (MADIT-CRT) (upper-right figure). Finally, cluster-wise event rates (composite of death or HF hospitalization) were computed for the combination of the two trials (bottom-left figure) and only considering subjects from ARIC (bottom-right figure). Results The visualisation of the low-dimensional space (upper-left figure) showed a clear aggregation of individuals according to the study, highlighting their different clinical and deformation properties. The individuals located around the MADIT-CRT patients (predominantly in cluster 3) showed the highest event rate (26.6%, similar to the MADIT-CRT event rate 25.4%) while those around the majority of the ARIC cohort showed the lowest rates (5.3%, similar to the ARIC event rate 5.7%). The MADIT-CRT-like ARIC individuals showed a much higher event-rate compared to the one expected from the cohort (21.1% vs 5.7%). Figure 1 Conclusion Our results serve as a proof-of-concept that unsupervised ML based analysis of complex clinical and imaging data can be used to integrate patient-based data, including complex echocardiographic data, to project individuals onto a multi-dimensional space with event rates that track with multidimensional location. Acknowledgement/Funding ARIC and TOPCAT were funded by the National Heart, Lung and Blood Institute, MADIT-CRT by Boston Scientific

scholarly journals Fostering Well-Being in the Elderly: Translating Theories on Positive Aging to Practical Approaches

2021 ◽  
Vol 8 ◽  
Author(s):  
Liora Bar-Tur
Keyword(s):  
Well Being ◽  
The Elderly ◽  
Community Dwelling ◽  
Community Centers ◽  
Aging Research ◽  
Positive Aging ◽  
Wide Range ◽  
Future Challenges ◽  
Sheltered Homes

This article overviews positive aging concepts and strategies to enhance well-being in the elderly and then presents a translation of theories on positive aging to practical approaches for Positive Aging. Drawing upon positive psychology and positive aging research and tools, this program is designed to help older adults improve their well-being by acquiring skills and strategies to cope with present and future challenges. The Mental Fitness Program for Positive Aging (MFPPA) can enhance seniors' quality of life by increasing their vital involvement and active engagement in life. This model is most appropriate for community dwelling individuals. It can easily be conducted in wide range of adult education programs in community centers, sheltered homes, and primary care clinics. It can also be conducted through online psychoeducational training.

scholarly journals A Survey on Artificial Intelligence Overview

2020 ◽  
Author(s):  
Aggarwal AJuhi ◽  
Shailesh Kumar
Keyword(s):  
Artificial Intelligence ◽  
Computer Vision ◽  
Expert System ◽  
Pattern Matching ◽  
Machine Intelligence ◽  
Human Beings ◽  
Matching Method ◽  
System P ◽  
Wide Range ◽  
Computational Relationship

Artificial Intelligence (AI) is the branch of computer science concerned with the study and creation of computer of computer system are more intelligence than human. Artificial Intelligence programmed by the human beings. We can increase the AI’s capabilities by the supervised and unsupervised teaching. Artificial Intelligence works with pattern matching method which attempts to describe objects, events or process in terms of their qualitative features, logical and computational relationship. AI can also be used to make predications in future. Artificial Intelligence helps people to make their tasks easily and efficiently. Intelligence is the way of thinking and acting upon the environment, this might depend upon the the programming. There is huge difference on the Natural Intelligence (NI), Machine Intelligence (MI) and Artificial Intelligence. There is wide range of application for that ranges from computer vision to expert system.

Sign in / Sign up

Export Citation Format

Share Document