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Found 6319 publications

Natural Resources for Human Health: A New Interdisciplinary Journal Dedicated to Natural Sciences

Gautam Sethi Zhaojun Wei Barbara Sawicka Bharat B. Aggarwal In Ho Kim Chunpeng Wan Karel Šmejkal Haipeng Lv Jialin Xu Rasul Suleria Zhiling Yu Visweswara Rao Ren Wang Mohammad Amjad Kamal Tarun Belwal Onur Bender Ihosvany Camps Jaruporn Rakmai Si Mi Andrei Mocan Shafi Ullah Khan Dongdong Wang Jianbo Xiao Carlos L.Cespedes Acuña Ana Sanches Silva Hafiz Ansar Ricardo DG De Albuquerque Diego Jelena Popovićdjordjević Vince Ördög Alessandra Cincinelli Michał Tomczyk Adriano Mollica Jesus Simal-Gandara Satyajit D. Sarker Gökhan Zengin Ashwell R. Ndhlala Manoj G. Kulkarni Claudio Ferrante

Publication Name: Natural Resources for Human Health

Publication Date: 2021-08-01

Volume: 1

Issue: 1

Page Range: 1-2

Description:

No description provided

Open Access: Yes

DOI: 10.53365/nrfhh/141005

The Role of Micronutrients to Support Immunity for COVID-19 Prevention

Mukhtar H. Ahmed Judit Molnár Arez Hassan

Publication Name: Revista Brasileira De Farmacognosia

Publication Date: 2021-08-01

Volume: 31

Issue: 4

Page Range: 361-374

Description:

The World Health Organization declared the novel coronavirus, named as SARS-CoV-2, as a global pandemic in early 2020 after the disease spread to more than 180 countries leading to tens of thousands of cases and many deaths within a couple of months. Consequently, this paper aims to summarize the evidence for the relationships between nutrition and the boosting of the immune system in the fight against the disease caused by SARS-CoV-2. This review, in particular, assesses the impact of vitamin and mineral supplements on the body’s defence mechanisms against SARS-CoV-2. The results revealed that there is a strong relationship between the ingestion of biological ingredients like vitamins C–E, and minerals such as zinc, and a reduction in the effects of coronavirus infection. These can be received from either nutrition rich food sources or from vitamin supplements. Furthermore, these macromolecules might have roles to play in boosting the immune response, in the healing process and the recovery time. Hence, we recommend that eating healthy foods rich in vitamins C–E with zinc and flavonoids could boost the immune system and consequently protect the body from serious infections. Graphical Abstract: [Figure not available: see fulltext.].

Open Access: Yes

DOI: 10.1007/s43450-021-00179-w

Vehicle occupant safety development with finite element method

István Lakatos Laszlo Porkolab

Publication Name: Pollack Periodica

Publication Date: 2021-08-01

Volume: 16

Issue: 2

Page Range: 30-35

Description:

Crash tests of vehicles are specified by government programs. This laws are includes only minimum requirements for individual components. Therefore additional consumer protection load cases have been developed by independent private institutes. Finite element method simulations can reduce development periods and the number of cost-intensive real crash tests. The goals of the calculations are that the early detection of component failure, the protection of occupants or pedestrians. The biggest challenge of the future, in the field of vehicle occupant safety is the interaction of the airbags and belt system with dummy by the electric vehicles, which have the concept of autonomous driving function. The aim of the research is to investigate this area using a simulation model.

Open Access: Yes

DOI: 10.1556/606.2021.00306

Performance evaluation of DNS servers to build a benchmarking system of DNS64 implementations

Keiichi Shima Attila Pivoda Gábor Lencse

Publication Name: Telecommunication Systems

Publication Date: 2021-08-01

Volume: 77

Issue: 4

Page Range: 643-653

Description:

DNS64 is an important IPv6 transition technology that facilitates the communication of an IPv6 only client with an IPv4 only server, which becomes a more and more common scenario. Several different DNS64 implementations exist, and their performance is a relevant decision factor for network operators. RFC 8219 has defined a benchmarking methodology for DNS64 servers, which requires the operation of an authoritative DNS server at 220% of the query rate used for DNS64 benchmarking. In this paper, we aim to build an authoritative DNS server that operates at 2.2 million qps (queries per second) rate, thus it facilitates DNS64 benchmarking up to 1,000,000 qps rate. To that end, we compare the performance of BIND, YADIFA, NSD, Knot DNS and FakeDNS (a special purpose software) to find the best suiting one of them. We fully disclose the details of our measurements including the configuration of the DNS implementations, the usage of our improved software tester called dns64perf ++, and the details of the hardware and software measurement environment in the NICT StarBED, Japan. We perform a series of measurements to examine, how the performance of the tested solutions scale up with the number of the active CPU cores from 1 to 32. Besides their performance, we also measure their memory consumption and zone load time. We present and discuss all the results. In addition to successfully building an authoritative DNS server with the required performance, we also make recommendations, which solutions suit to different special needs.

Open Access: Yes

DOI: 10.1007/s11235-021-00780-3

Segmentation of a road vehicle vibration signal using multiple comparison procedures between paired samples

László Róbert Hári

Publication Name: Tehnicki Vjesnik

Publication Date: 2021-08-01

Volume: 28

Issue: 5

Page Range: 1597-1604

Description:

Segmentation of road vehicle vibration (RVV) signals can occur by the need to analyse or synthesise vibrations obtained in passenger cars or on the stowage of vans, trucks. A general and widely used measure to quantify RVV signals is its description via power spectral density (PSD). From a given PSD a Gaussian signal can be generated in a shaker testing laboratory. However, actual RVVs tend to have a non-Gaussian and nonstationary nature, which can be modelled as a composition of different segments, each with a different length and RMS content. For simulation purposes of nonstationary vibration signals, different approaches have been introduced yet each with its unique signal segmentation approaches. The current paper proposes a signal segmentation method implemented in the time-frequency domain in order to find segments within an RVV signal, where each segment has similarity in-between and is dissimilar to neighbouring segments. For this purpose, multiple comparison tests had been utilised between the Short-time Fourier transforms (STFT) applied on given fractions of an RVV. Different countermeasures had been applied against the Type I. error inflation.

Open Access: Yes

DOI: 10.17559/TV-20200122112551

Two Stages Outlier Removal as Pre-Processing Digitizer Data on Fine Motor Skills (FMS) Classification Using Covariance Estimator and Isolation Forest

Surya Sumpeno A. Tormási Nurul Zainal Fanani Festa Yumpi Rahmanawati K. Khamid Adri Gabriel Sooai Mauridhi Hery Purnomo Ĺaszĺo T. Ḱoczy

Publication Name: International Journal of Intelligent Engineering and Systems

Publication Date: 2021-08-01

Volume: 14

Issue: 4

Page Range: 571-582

Description:

The increase of the classification accuracy level has become an important problem in machine learning especially in diverse data-set that contain the outlier data. In the data stream or the data from sensor readings that produce large data, it allows a lot of noise to occur. It makes the performance of the machine learning model is disrupted or even decreased. Therefore, clean data from noise is needed to obtain good accuracy and to improve the performance of the machine learning model. This research proposes a two-stages for detecting and removing outlier data by using the covariance estimator and isolation forest methods as pre-processing in the classification process to determine fine motor skill (FMS). The dataset was generated from the process of recording data directly during cursive writing by using a digitizer. The data included the relative position of the stylus on the digitizer board. x position, y position, z position, and pressure values are then used as features in the classification process. In the process of observation and recording, the generated data was very huge so some of them produce the outlier data. From the experimental results that have been implemented, the level of accuracy in the FMS classification process increases between 0.5-1% by using the Random Forest classifier after the detection and outlier removal by using covariance estimator and isolation forest. The highest accuracy rate achieves 98.05% compared to the accuracy without outlier removal, which is only about 97.3%.

Open Access: Yes

DOI: 10.22266/ijies2021.0831.50

Influence of imperfections in the buckling resistance of steel beam-columns under fire

Samer Nemer F. Papp

Publication Name: Pollack Periodica

Publication Date: 2021-08-01

Volume: 16

Issue: 2

Page Range: 1-6

Description:

This paper presents an investigation on the influence of structural imperfections on the ultimate load capacity of steel welded beam-columns with class 4 cross-section under elevated temperatures. This is done by considering different amplitudes for the global and local (plate) imperfections, and different residual stresses distributions available in the literature. To this purpose, a geometrically and materially non-linear finite element model using Abaqus software has been used to determine the buckling resistance of a steel welded beam-column at elevated temperatures, using the material properties of EN1993-1-2. The imperfection sensitivity of beam-columns is reported: the influences of the amplitudes of the geometric imperfection and the patterns of the residual stress on the load capacity are compared.

Open Access: Yes

DOI: 10.1556/606.2021.00303

Application of structural entropy and spatial filling factor in colonoscopy image classification

Brigita Sziová Zoltán Fazekas Szilvia Nagy

Publication Name: Entropy

Publication Date: 2021-08-01

Volume: 23

Issue: 8

Page Range: Unknown

Description:

For finding colorectal polyps the standard method relies on the techniques and devices of colonoscopy and the medical expertise of the gastroenterologist. In case of images acquired through colonoscopes the automatic segmentation of the polyps from their environment (i.e., from the bowel wall) is an essential task within computer aided diagnosis system development. As the number of the publicly available polyp images in various databases is still rather limited, it is important to develop metaheuristic methods, such as fuzzy inference methods, along with the deep learning algorithms to improve and validate detection and classification techniques. In the present manuscript firstly a fuzzy rule set is generated and validated. The former process is based on a statistical approach and makes use of histograms of the antecedents. Secondly, a method for selecting relevant antecedent variables is presented. The selection is based on the comparision of the histograms computed from the measured values for the training set. Then the inclusion of the Rényi-entropy-based structural entropy and the spatial filling factor into the set of input variables is proposed and assessed. The beneficial effect of including the mentioned structural entropy of the entropies from the hue and saturation (H and S) colour channels resulted in 65% true positive and 60% true negative rate of the classification for an advantageously selected set of antecedents when working with HSV images.

Open Access: Yes

DOI: 10.3390/e23080936

Bananas, coffee and palm oil: The trade of agricultural commodities in the framework of the EU-Colombia free trade agreement

Laszlo Vasa Béla Soltész Julieth P.T. Cubillos

Publication Name: Plos One

Publication Date: 2021-08-01

Volume: 16

Issue: 8 August

Page Range: Unknown

Description:

Generally, research and studies about commodities focus on price trends, analysis in terms of international competitiveness, market position structure, rate of net exports, market share, and concentration index. This paper has developed an analysis of the most influential agricultural commodities traded from Colombia to European Union, which are bananas, coffee, and palm oil. Analyzing the economic and commercial effects in two traditional agricultural commodities from Colombia (bananas and coffee) with the rise of palm oil as a commodity in the trade relation with its partner; the European Union. The structure draws from the overview of general aspects and the behavior of Colombian foreign trade, as diversification of export products and trade partners, to focus on the characteristics of the trade relationship between the European Union and Colombia. The aim is analyze the proportional relation between bananas, coffee, and palm oil exported to the EU, according to three indicators, the volume of production, exports share, and trade value, from 2008 until 2019, identifying the trends before and after the implementation of the free trade agreement. Finally, with the coefficient correlation, determine the agricultural commodity that has the strongest and positive relationship with the total agricultural exports value from Colombia to the European Union.

Open Access: Yes

DOI: 10.1371/journal.pone.0256242