Bioinformatics Analysis of Linear B-cell Viscumin Toxin Epitope With Potential Use in Molecularly Imprinted Polymer Biosensors

Background: There are many diseases around the world that threaten human health and its related hygienic issues. Cancer is among the conditions mentioned above that cause many problems for health sectors worldwide.Methods: The present research analyzed the linear B-cell epitope of viscumin from European mistletoe using bioinformatics tools. We also provided references for the fast detection of biological agents. Several important tools, such as Protparam, NCBI, PDB, T-coffee, BCpred, Bptope, Ellipro, and Cn3D were used to predict the viscumin linear epitope and its physical and chemical properties.Results: The 9-mer epitope found as QQTTGEEYF embedded in the A-chain of protein by the least sequence homology with other homologous rivals. Its molecular weight, theoretical isoelectric point, and the total number of negatively charged residues were 1102.1, 3.79, and 2, respectively.Conclusion: Using different databases and establishing the accuracy level of ˃50% for linear B-cell epitope prediction, the selected epitope passed the related criteria and was introduced as a new linear epitope as a potential biological element in biosensors for cancer (viscumin) fast therapeutic detection

Un análisis contrastivodel orden de las palabras, de los verbos y de los tiempos verbales en mazandaraní, farsi y inglés

This study deals with contrasting three languages, namely English, Farsi (Persian), and Mazandarani (Tabari). The study followed two main goals: first, providing Mazandarani and Farsi teachers with pedagogical implications in teaching English as a foreign language (EFL); and second, taking a step toward preventing the Mazandarani (Mazani) language from gradual extinction. By comparing the word order, verbs, and tenses of the three aforementioned languages, it was concluded that in some cases Mazandarani, and in other cases Farsi, is more similar to English. With respect to word order, Mazandarani and Farsi are SOV but English is SVO. Regarding verbs and tenses, contrary to English, Mazandarani and Farsi are inflected. This inflection plays an important role in forming different tenses in the conjugation process.Este estudio contrasta tres idiomas: el inglés, el farsi (persa) y el mazandaraní (Tabari). Se plantea dos objetivos principales: por un lado, ofrecer a los maestros de mazandaraní y de farsi implicaciones pedagógicas cuando enseñan el inglés como lengua extranjera (EFL); y, el segundo, colaborar en los mecanismo de prevención de la lengua mazandaraní (Mazani) de su extinción gradual. Al comparar el orden de las palabras, los verbos y los tiempos de los tres idiomas antes mencionados, se concluye que, en algunos casos el mazandaraní, y en otros casos, el Farsi, son más similares al inglés. En cuanto al orden de las palabras, el mazandaraní y persa son lenguas SOV, mientras que el inglés es SVO. En cuanto a los verbos y tiempos verbales, a diferencia del inglés, el farsi y el mazandaraní son lenguas flexivas. Esta flexión juega un papel importante en la formación de diferentes tiempos verbales en el proceso de conjugación

Lossy Filter Synthesis

All telecommunication systems, such as cellular mobile networks (cellphones), object-detection systems (radars), and navigation systems that include satellite positioning systems (GPS), base their functioning on radio wave radiation with pre-defined frequencies and thus require a microwave filter to select the most appropriate frequencies. Generally speaking, the more highly-selective a filter is, the less non-useful frequencies and interference it picks up. Recent advances in microwave instruments, semiconductors, fabrication technologies and microwave filters applications have ushered in a new era in performance but have also brought significant challenges, such as keeping fabrication costs low, miniaturizing, and making low-profile devices. These challenges must be met while at the same time maintaining the performance of conventional devices. The thesis proposes use of lossy filter concepts to maintain high quality filtering frequency response flatness and selectivity regardless of the filter’s physical size. The method is applied to lumped element filters. It introduces resistances to the physical structure of the filter and hence a certain amount of loss to the frequency response of the filter. The lossy filter synthesis is based on the coupling matrix mode. The thesis also proposes modifications to the traditional lossy filter design techniques, to improve the filter performance in the stopband

Trace determination of paraben in artificial saliva spray with gold nanoparticle assisted and head space gas chromatography

Abstract Introduction: Preservatives such as parabens in health products and pharmaceuticals cause different diseases and cancers in humans. It is very important to study and control the content of this substance in pharmaceutical preparations, and in particular artificial saliva sprays. The proposed method is a nanotechnology-based methodology that can help to achieve useful results in the field of quick and accurate control of health-related products. Also, comparable figures of merit are predicted using this method. Methods and Results:In this research, the determination and measurement of paraben in the formulation of the drug products- artificial saliva spray- by headspace gas chromatography method using the simplicity of the matrix headspace as well as free from the complexity of the matrix of the sample, gas chromatography system is provided with the aid of a nano-scale catalyst. This approach is a new trend in the saliva matrix in Iran and around the world. In recent years, many studies have been conducted on the analysis of parabens in cosmetics and pharmaceutical  products. Despite these studies, research on the determination of parabens to increase the sensitivity and precision of the method is still limited. The application of gold nanoparticles with a new approach in terms of using expired pharmaceutical waste for functionalization of gold nanoparticle and applying this method to the preparation of nano-catalysts would results in the creation of an appropriate added value and reduce the final cost of production. Conclusions:Generally, sulfuric acid and para-toluene sulfonic acid are used as catalysts for the sterilization reactions. In this study, the use of functionalized nanoparticles with a novel approach, in the form of utilization of expired pharmaceutical waste (L-cysteine) for the preparation of nano-catalysts, was evaluated. This novel method of nano-catalyst production can create an appropriate added value and lowers the cost of finished products. The application of a nanoscale catalyst can be a novel method with acceptable accuracy to measure preservatives such as parabens in complex environments. &nbsp

Solution for remote real-time visual expertise of agricultural objects

ArticleIn recent years automated image and video analyses of plants and animals have become important techniques in Pre cision Agriculture for the detection of anomalies in development. Unlikely, machine learning (i.e., artificial neural networks, support vector machine, and other relevant techniques) are not always able to support decision making. Nevertheless, experts can use these techniques for developing more precise solutions and analysis approaches. It is labour - intensive and time - consuming for the experts to continuously visit the production sites to make direct on - site observations. Therefore, videos from the site n eed to be made available for remote viewing and analysis. In some cases it is also essential to monitor different parts of objects in agriculture and animal farming (e.g., bottom of the plants, stomach of the animal, etc.) which are difficult to access in standard recording procedures. One possible solution for the farmer is the use of a portable camera with real - streaming option r ather than a stationary camera. The aim of this paper is the proposition of a solution for real - time video streaming of agricultural objects (plants and/or animals) for remote expert evaluation and diagnosis. The proposed system is based on a Raspberry Pi 3, which is used to transfer the video from the attached camera to the YouTube streaming service. Users will be able to watch the video stream from the YouTube service on any device that has a web browser. Several cameras (USB, and Raspberry Pi camera) and video resolutions (from 480p till 1 , 080p) are compared and analysed, to find the best option, taking into account video quality, frame rates, and latency. Energy consumption of the whole system is evaluated and for the chosen solution it is 645 mA

Development of an Optical System Based on Spectral Imaging Used for a Slug Control Robot

The state-of-the-art technique to control slug pests in agriculture is the spreading of slug pellets. This method has some downsides, because slug pellets also harm beneficials and often fail because their efficiency depends on the prevailing weather conditions. This study is part of a research project which is developing a pest control robot to monitor the field, detect slugs, and eliminate them. Robots represent a promising alternative to slug pellets. They work independent of weather conditions and can distinguish between pests and beneficials. As a prerequisite, a robot must be able to reliably identify slugs irrespective of the characteristics of the surrounding conditions. In this context, the utilization of computer vision and image analysis methods are challenging, because slugs look very similar to the soil, particularly in color images. Therefore, the goal of this study was to develop an optical filter-based system that distinguishes between slugs and soil. In this context, the spectral characteristics of both slugs and soil in the visible and visible near-infrared (VNIR) wavebands were measured. Conspicuous maxima followed by conspicuous local minima were found for the reflection spectra of slugs in the near infrared range from 850 nm to 990 nm]. Thus, this enabled differentiation between slugs and soils; soils showed a monotonic increase in the intensity of the relative reflection for this wavelength. The extrema determined in the reflection spectra of slugs were used to develop and set up a slug detector device consisting of a monochromatic camera, a filter changer and two narrow bandpass filters with nominal wavelengths of 925 nm and 975 nm. The developed optical system takes two photographs of the target area at night. By subtracting the pixel values of the images, the slugs are highlighted, and the soil is removed in the image due to the properties of the reflection spectra of soils and slugs. In the resulting image, the pixels of slugs were, on average, 12.4 times brighter than pixels of soil. This enabled the detection of slugs by a threshold method.Peer Reviewe

Drone-Based Cattle Detection Using Deep Neural Networks

© 2021, Springer Nature Switzerland AG. Cattle form an important source of farming in many countries. In literature, several attempts have been conducted to detect farm animals for different applications and purposes. However, these approaches have been based on detecting animals from images captured from ground level and most approaches use traditional machine learning approaches for their automated detection. In this modern era, Drones facilitate accessing images in challenging environments and scanning large-scale areas with minimum time, which enables many new applications to be established. Considering the fact that drones typically are flown at high altitude to facilitate coverage of large areas within a short time, the captured object size tend to be small and hence this significantly challenges the possible use of traditional machine learning algorithms for object detection. This research proposes a novel methodology to detect cattle in farms established in desert areas using Deep Neural Networks. We propose to detect animals based on a ‘group-of-animals’ concept and associated features in which different group sizes and animal density distribution are used. Two state-of-the-art Convolutional Neural Network (CNN) architectures, SSD-500 and YOLO V-3, are effectively configured, trained and used for the purpose and their performance efficiencies are compared. The results demonstrate the capability of the two generated CNN models to detect groups-of-animals in which the highest accuracy recorded was when using SSD-500 giving a F-score of 0.93, accuracy of 0.89 and mAP rate of 84.7

Åtgärder för att förbättra boxhygien och reducera ammoniakemission i konventionella slaktgrisboxar

Genom att duscha vatten över spaltgolvet får grisarna möjlighet att blöta huden och därmed öka värmeavgivningen under varma perioder. Systemet ändrar var i boxen grisarna väljer att ligga så att de ligger mindre på spaltgolvet och mer på liggytan. När spaltgolvet inte är upptaget av liggande grisar tvingas inte grisarna att gödsla/urinera på den fasta liggytan. Därmed förbättras boxhygienen och ammoniakförlusterna minskar. Ökad lufthastighet på liggytan ger också grisarna bättre möjlighet till kylning, vilket medför bättre boxhygien och mindre ammoniakförluster. Detta är två metoder att kyla grisarna som kan utföras i befintliga stallar. Åtgärderna har studerats under två varma sommarperioder i ett EU-projekt med samarbete mellan sex lände

A concept for application of integrated digital technologies to enhance future smart agricultural systems

Future agricultural systems should increase productivity and sustainability of food production and supply. For this, integrated and efficient capture, management, sharing, and use of agricultural and environmental data from multiple sources is essential. However, there are challenges to understand and efficiently use different types of agricultural and environmental data from multiple sources, which differ in format and time interval. In this regard, the role of emerging technologies is considered to be significant for integrated data gathering, analyses and efficient use. In this study, a concept was developed to facilitate the full integration of digital technologies to enhance future smart and sustainable agricultural systems. The concept has been developed based on the results of a literature review and diverse experiences and expertise which enabled the identification of stat-of-the-art smart technologies, challenges and knowledge gaps. The features of the proposed solution include: data collection methodologies using smart digital tools; platforms for data handling and sharing; application of Artificial Intelligent for data integration and analysis; edge and cloud computing; application of Blockchain, decision support system; and a governance and data security system. The study identified the potential positive implications i.e. the implementation of the concept could increase data value, farm productivity, effectiveness in monitoring of farm operations and decision making, and provide innovative farm business models. The concept could contribute to an overall increase in the competitiveness, sustainability, and resilience of the agricultural sector as well as digital transformation in agriculture and rural areas. This study also provided future research direction in relation to the proposed concept. The results will benefit researchers, practitioners, developers of smart tools, and policy makers supporting the transition to smarter and more sustainable agriculture systems

A concept for application of integrated digital technologies to enhance future smart agricultural systems

Publication history: Accepted - 16 may 2023; Published - 17 May 2023.Future agricultural systems should increase productivity and sustainability of food production and supply. For this, integrated and efficient capture, management, sharing, and use of agricultural and environmental data from multiple sources is essential. However, there are challenges to understand and efficiently use different types of agricultural and environmental data from multiple sources, which differ in format and time interval. In this regard, the role of emerging technologies is considered to be significant for integrated data gathering, analyses and efficient use. In this study, a concept was developed to facilitate the full integration of digital technologies to enhance future smart and sustainable agricultural systems. The concept has been developed based on the results of a literature review and diverse experiences and expertise which enabled the identification of stat-of-the-art smart technologies, challenges and knowledge gaps. The features of the proposed solution include: data collection methodologies using smart digital tools; platforms for data handling and sharing; application of Artificial Intelligent for data integration and analysis; edge and cloud computing; application of Blockchain, decision support system; and a governance and data security system. The study identified the potential positive implications i.e. the implementation of the concept could increase data value, farm productivity, effectiveness in monitoring of farm operations and decision making, and provide innovative farm business models. The concept could contribute to an overall increase in the competitiveness, sustainability, and resilience of the agricultural sector as well as digital transformation in agriculture and rural areas. This study also provided future research direction in relation to the proposed concept. The results will benefit researchers, practitioners, developers of smart tools, and policy makers supporting the transition to smarter and more sustainable agriculture systems