scholarly journals A Review About Preparation and Properties of Biochar and Application Fields in the Environment

2021 ◽  
Vol 39 (12) ◽  
pp. 1894-1904
Author(s):  
Marwa Al Rawi ◽  
Ghayda Al Kindi ◽  
Jwad Al Refaae
Keyword(s):  
Application Fields

The First Experience with new Small-Sized Commercial Tem (TEM -100) and Biological Specimens

1990 ◽  
Vol 48 (1) ◽  
pp. 611-611
Author(s):  
Jovan Vukovié
Keyword(s):  
Electron Microscopy ◽  
Electron Microscope ◽  
Liquid Nitrogen ◽  
Boiling Temperature ◽  
Resolution Power ◽  
Application Fields ◽  
Working Liquid

Conventional electron microscope TEM -100 (Made by “ELECTRON”, Sumy, USSR; Fig. 1) was presented at the XI Int. Congress on Electron Microscopy (Kyoto) by I.S. Lyalko et al. (1,2). The purpose of the microscope constructors were to design a small-sized general conventional TEM for various application fields. The microscope have mini lenses, which winding is placed in closed casing and soaked in working liquid (low boiling temperature) but upper part of the casing being water cooled.In this communication we gave our first experience and impression as a customer, beginning from the montage, the instruction and the testing of the microscope to our application in the field of biological specimens. Just after montage of the microscope on the second floor, the test of the point resolution power was performed by Ir specimen. It was achieved 0.5 nm (Fig. 2 and 3) on the roll film (ORWO 22 DIN) with 300 OOOx magnification and anticontamination device. The ultimate vacuum (about 10exp-6 mm Hg, ion discharge pump) also achieved using large trap cooled by liquid nitrogen.

Nested code sequences of Barker — Mersenne — Raghavarao

2019 ◽  
pp. 71-81
Author(s):  
M. B. Sergeev ◽  
V. A. Nenashev ◽  
A. M. Sergeev
Keyword(s):  
Data Transfer ◽  
Radio Channel ◽  
Main Peak ◽  
Synthesis Methods ◽  
Orthogonal Matrices ◽  
Useful Signal ◽  
New Codes ◽  
Increase In Accuracy ◽  
Application Fields ◽  
Barker Codes

Introduction: The problem of noise-free encoding for an open radio channel is of great importance for data transfer. The results presented in this paper are aimed at stimulating scientific interest in new codes and bases derived from quasi-orthogonal matrices, as a basis for the revision of signal processing algorithms.Purpose: Search for new code sequences as combinations of codes formed from the rows of Mersenne and Raghavarao quasi-orthogonal matrices, as well as complex and more efficient Barker — Mersenne — Raghavarao codes.Results: We studied nested code sequences derived from the rows of quasi-orthogonal cyclic matrices of Mersenne, Raghavarao and Hadamard, providing estimates for the characteristics of the autocorrelation function of nested Barker, Mersenne and Raghavarao codes, and their combinations: in particular, the ratio between the main peak and the maximum positive and negative “side lobes”. We have synthesized new codes, including nested ones, formed on the basis of quasi-orthogonal matrices with better characteristics than the known Barker codes and their nested constructions. The results are significant, as this research influences the establishment and development of methods for isolation, detection and processing of useful information. The results of the work have a long aftermath because new original code synthesis methods need to be studied, modified, generalized and expanded for new application fields.Practical relevance: The practical application of the obtained results guarantees an increase in accuracy of location systems, and detection of a useful signal in noisy background. In particular, these results can be used in radar systems with high distance resolution, when detecting physical objects, including hidden ones.

Programmable Integrated Photonics

2020 ◽  
Author(s):  
José Capmany ◽  
Daniel Pérez
Keyword(s):  
Integrated Circuit ◽  
Performance Monitoring ◽  
Low Cost ◽  
Limiting Factors ◽  
External Control ◽  
Integrated Photonics ◽  
New Paradigm ◽  
Photonic Integrated Circuit ◽  
And Performance ◽  
Application Fields

Programmable Integrated Photonics (PIP) is a new paradigm that aims at designing common integrated optical hardware configurations, which by suitable programming can implement a variety of functionalities that, in turn, can be exploited as basic operations in many application fields. Programmability enables by means of external control signals both chip reconfiguration for multifunction operation as well as chip stabilization against non-ideal operation due to fluctuations in environmental conditions and fabrication errors. Programming also allows activating parts of the chip, which are not essential for the implementation of a given functionality but can be of help in reducing noise levels through the diversion of undesired reflections. After some years where the Application Specific Photonic Integrated Circuit (ASPIC) paradigm has completely dominated the field of integrated optics, there is an increasing interest in PIP justified by the surge of a number of emerging applications that are and will be calling for true flexibility, reconfigurability as well as low-cost, compact and low-power consuming devices. This book aims to provide a comprehensive introduction to this emergent field covering aspects that range from the basic aspects of technologies and building photonic component blocks to the design alternatives and principles of complex programmable photonics circuits, their limiting factors, techniques for characterization and performance monitoring/control and their salient applications both in the classical as well as in the quantum information fields. The book concentrates and focuses mainly on the distinctive features of programmable photonics as compared to more traditional ASPIC approaches.

scholarly journals Multi-Agent Reinforcement Learning: A Review of Challenges and Applications

2021 ◽  
Vol 11 (11) ◽  
pp. 4948
Author(s):  
Lorenzo Canese ◽  
Gian Carlo Cardarilli ◽  
Luca Di Di Nunzio ◽  
Rocco Fazzolari ◽  
Daniele Giardino ◽  
...  
Keyword(s):  
Reinforcement Learning ◽  
Mathematical Models ◽  
Learning Algorithms ◽  
Single Agent ◽  
Critical Issues ◽  
Multi Agent ◽  
Pros And Cons ◽  
Application Fields

In this review, we present an analysis of the most used multi-agent reinforcement learning algorithms. Starting with the single-agent reinforcement learning algorithms, we focus on the most critical issues that must be taken into account in their extension to multi-agent scenarios. The analyzed algorithms were grouped according to their features. We present a detailed taxonomy of the main multi-agent approaches proposed in the literature, focusing on their related mathematical models. For each algorithm, we describe the possible application fields, while pointing out its pros and cons. The described multi-agent algorithms are compared in terms of the most important characteristics for multi-agent reinforcement learning applications—namely, nonstationarity, scalability, and observability. We also describe the most common benchmark environments used to evaluate the performances of the considered methods.

scholarly journals Penalized partial least squares for pleiotropy

2021 ◽  
Vol 22 (1) ◽  
Author(s):  
Camilo Broc ◽  
Therese Truong ◽  
Benoit Liquet
Keyword(s):  
Least Squares ◽  
Partial Least Squares ◽  
Association Studies ◽  
A Priori ◽  
Simulated Data ◽  
Real Data ◽  
Genome Wide Association Studies ◽  
Genetic Associations ◽  
Multiple Traits ◽  
Application Fields

Abstract Background The increasing number of genome-wide association studies (GWAS) has revealed several loci that are associated to multiple distinct phenotypes, suggesting the existence of pleiotropic effects. Highlighting these cross-phenotype genetic associations could help to identify and understand common biological mechanisms underlying some diseases. Common approaches test the association between genetic variants and multiple traits at the SNP level. In this paper, we propose a novel gene- and a pathway-level approach in the case where several independent GWAS on independent traits are available. The method is based on a generalization of the sparse group Partial Least Squares (sgPLS) to take into account groups of variables, and a Lasso penalization that links all independent data sets. This method, called joint-sgPLS, is able to convincingly detect signal at the variable level and at the group level. Results Our method has the advantage to propose a global readable model while coping with the architecture of data. It can outperform traditional methods and provides a wider insight in terms of a priori information. We compared the performance of the proposed method to other benchmark methods on simulated data and gave an example of application on real data with the aim to highlight common susceptibility variants to breast and thyroid cancers. Conclusion The joint-sgPLS shows interesting properties for detecting a signal. As an extension of the PLS, the method is suited for data with a large number of variables. The choice of Lasso penalization copes with architectures of groups of variables and observations sets. Furthermore, although the method has been applied to a genetic study, its formulation is adapted to any data with high number of variables and an exposed a priori architecture in other application fields.

scholarly journals Inertial Measurement Unit Sensors in Assistive Technologies for Visually Impaired People, a Review

Sensors ◽  
2021 ◽  
Vol 21 (14) ◽  
pp. 4767
Author(s):  
Karla Miriam Reyes Leiva ◽  
Milagros Jaén-Vargas ◽  
Benito Codina ◽  
José Javier Serrano Olmedo
Keyword(s):  
Inertial Measurement Unit ◽  
Visually Impaired ◽  
Inertial Sensors ◽  
Assistive Technologies ◽  
Biomechanical Analysis ◽  
Measurement Unit ◽  
Inertial Measurement ◽  
Visually Impaired People ◽  
Impaired People ◽  
Application Fields

A diverse array of assistive technologies have been developed to help Visually Impaired People (VIP) face many basic daily autonomy challenges. Inertial measurement unit sensors, on the other hand, have been used for navigation, guidance, and localization but especially for full body motion tracking due to their low cost and miniaturization, which have allowed the estimation of kinematic parameters and biomechanical analysis for different field of applications. The aim of this work was to present a comprehensive approach of assistive technologies for VIP that include inertial sensors as input, producing results on the comprehension of technical characteristics of the inertial sensors, the methodologies applied, and their specific role in each developed system. The results show that there are just a few inertial sensor-based systems. However, these sensors provide essential information when combined with optical sensors and radio signals for navigation and special application fields. The discussion includes new avenues of research, missing elements, and usability analysis, since a limitation evidenced in the selected articles is the lack of user-centered designs. Finally, regarding application fields, it has been highlighted that a gap exists in the literature regarding aids for rehabilitation and biomechanical analysis of VIP. Most of the findings are focused on navigation and obstacle detection, and this should be considered for future applications.

scholarly journals A Multi Objective Evolutionary Algorithm for the Parameters Extraction of Organic Thin Film Transistors Models

Electronics ◽  
2021 ◽  
Vol 10 (8) ◽  
pp. 939
Author(s):  
Rosario Schiano Lo Moriello ◽  
Davide Ruggiero ◽  
Leopoldo Angrisani ◽  
Enzo Caputo ◽  
Francesco de Pandi ◽  
...  
Keyword(s):  
Thin Film ◽  
Evolutionary Algorithm ◽  
Design Stage ◽  
Model Parameters ◽  
Organic Transistors ◽  
Organic Thin Film ◽  
Multi Objective ◽  
Application Fields ◽  
Channel Lengths ◽  
P Type

Thanks to their peculiar features, organic transistors are proving to be a valuable alternative to traditional semiconducting devices in several application fields; however, before releasing their exploitation, simulating their behaviour through adequate circuital models could be advisable during the design stage of electronic circuits and/or boards. Consequently, accurately extracting the parameter value of those models is fundamental to developing useful libraries for hardware design environments. To face the considered problem, the authors present a method based on successive application of Single- and Multi-Objective Evolutionary Algorithm for the optimal tuning of model parameters of organic transistors on thin film (OTFT). In particular, parameters are first roughly estimated to assure the best fit with the experimental transfer characteristics; the estimates are successively refined through the multi-objective strategy by also matching the values of the experimental mobility. The performance of the method has been assessed by estimating the parameters value of both P-type and N-type OTFTs characterized by different values of channel lengths; the obtained results evidence that the proposed method can obtain suitable parameters values for all the considered channel lengths.

scholarly journals Multi-Task Optimization and Multi-Task Evolutionary Computation in the Past Five Years: A Brief Review

Mathematics ◽  
2021 ◽  
Vol 9 (8) ◽  
pp. 864
Author(s):  
Qingzheng Xu ◽  
Na Wang ◽  
Lei Wang ◽  
Wei Li ◽  
Qian Sun
Keyword(s):  
Evolutionary Computation ◽  
Explicit Knowledge ◽  
Optimization Problems ◽  
Effective Means ◽  
Typical Application ◽  
The Past ◽  
Current State ◽  
Evolution Algorithms ◽  
Application Fields

Traditional evolution algorithms tend to start the search from scratch. However, real-world problems seldom exist in isolation and humans effectively manage and execute multiple tasks at the same time. Inspired by this concept, the paradigm of multi-task evolutionary computation (MTEC) has recently emerged as an effective means of facilitating implicit or explicit knowledge transfer across optimization tasks, thereby potentially accelerating convergence and improving the quality of solutions for multi-task optimization problems. An increasing number of works have thus been proposed since 2016. The authors collect the abundant specialized literature related to this novel optimization paradigm that was published in the past five years. The quantity of papers, the nationality of authors, and the important professional publications are analyzed by a statistical method. As a survey on state-of-the-art of research on this topic, this review article covers basic concepts, theoretical foundation, basic implementation approaches of MTEC, related extension issues of MTEC, and typical application fields in science and engineering. In particular, several approaches of chromosome encoding and decoding, intro-population reproduction, inter-population reproduction, and evaluation and selection are reviewed when developing an effective MTEC algorithm. A number of open challenges to date, along with promising directions that can be undertaken to help move it forward in the future, are also discussed according to the current state. The principal purpose is to provide a comprehensive review and examination of MTEC for researchers in this community, as well as promote more practitioners working in the related fields to be involved in this fascinating territory.

scholarly journals Ten Years of Lateral Flow Immunoassay Technique Applications: Trends, Challenges and Future Perspectives

Sensors ◽  
2021 ◽  
Vol 21 (15) ◽  
pp. 5185
Author(s):  
Fabio Di Nardo ◽  
Matteo Chiarello ◽  
Simone Cavalera ◽  
Claudio Baggiani ◽  
Laura Anfossi
Keyword(s):  
Environmental Control ◽  
Improve Patient Care ◽  
Turnaround Time ◽  
Lateral Flow ◽  
Lateral Flow Immunoassay ◽  
Future Perspectives ◽  
Immunoassay Technique ◽  
Food And Feed ◽  
Application Fields ◽  
Feed Safety

The Lateral Flow Immunoassay (LFIA) is by far one of the most successful analytical platforms to perform the on-site detection of target substances. LFIA can be considered as a sort of lab-in-a-hand and, together with other point-of-need tests, has represented a paradigm shift from sample-to-lab to lab-to-sample aiming to improve decision making and turnaround time. The features of LFIAs made them a very attractive tool in clinical diagnostic where they can improve patient care by enabling more prompt diagnosis and treatment decisions. The rapidity, simplicity, relative cost-effectiveness, and the possibility to be used by nonskilled personnel contributed to the wide acceptance of LFIAs. As a consequence, from the detection of molecules, organisms, and (bio)markers for clinical purposes, the LFIA application has been rapidly extended to other fields, including food and feed safety, veterinary medicine, environmental control, and many others. This review aims to provide readers with a 10-years overview of applications, outlining the trends for the main application fields and the relative compounded annual growth rates. Moreover, future perspectives and challenges are discussed.

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