Discovery of Single Nucleotide Polymorphisms and Mutations by Pyrosequencing

Comparative genomics, analyzing variation among individual genomes, is an area of intense investigation. DNA sequencing is usually employed to look for polymorphisms and mutations. Pyrosequencing, a real-time DNA sequencing method, is emerging as a popular platform for comparative genomics. Here we review the use of this technology for mutation scanning, polymorphism discovery and chemical haplotyping. We describe the methodology and accuracy of this technique and discuss how to reduce the cost for large-scale analysis

INVESTIGATING THE IMPACT OF ECONOMIC, POLITICAL, AND SOCIAL FACTORS ON AUGMENTED REALITY TECHNOLOGY ACCEPTANCE IN AGRICULTURE (LIVESTOCK FARMING) SECTOR IN DEVELOPING COUNTRIES

The discussion of the factors affecting the tendency to accept new technologies in developing countries is very important. Lack of use of modern technologies in developing countries, especially in the agricultural (livestock farming) sector, leads to negative effects on the quality and quantity of products and the country loses its ability to compete in the international arena. The main purpose of this study is to investigate the factors affecting on Augmented Reality technology acceptance in the agricultural (livestock) sector of Iran. In this research, the dependent variable is a qualitative variable that is classified into five levels based on the theory of experts using the SWARA method. The dependent variable indicates the ability (awareness) and capability (financially) of a person to accept AR technology. We used the Multinomial Logit model due to the dependent variable is nominal and has more than two categories. The results showed that, the variables of public participation, and education have a significant effect on the willingness to adopt Augmented Reality technology at all levels among farmers.  But variable costs and the number of family labor do not have a significant effect on the willingness to accept Augmented Reality technology. The policy recommendations of this research are that councils can play an important role in raising the level of public participation and conveying the demands of the people to the government. To do this, they must receive the necessary training in order to attract public participation. This is possible through training workshops to increase the level of farmers’ awareness. &nbsp

Towards Real-time Remote Processing of Laparoscopic Video

Laparoscopic surgery is a minimally invasive technique where surgeons insert a small video camera into the patient\u27s body to visualize internal organs and use small tools to perform these procedures. However, the benefit of small incisions has a disadvantage of limited visualization of subsurface tissues. Image-guided surgery (IGS) uses pre-operative and intra-operative images to map subsurface structures and can reduce the limitations of laparoscopic surgery. One particular laparoscopic system is the daVinci-si robotic surgical vision system. The video streams generate approximately 360 megabytes of data per second, demonstrating a trend toward increased data sizes in medicine, primarily due to higher-resolution video cameras and imaging equipment. Real-time processing this large stream of data on a bedside PC, single or dual node setup, may be challenging and a high-performance computing (HPC) environment is not typically available at the point of care. To process this data on remote HPC clusters at the typical 30 frames per second rate (fps), it is required that each 11.9 MB (1080p) video frame be processed by a server and returned within the time this frame is displayed or 1/30th of a second. The ability to acquire, process, and visualize data in real time is essential for the performance of complex tasks as well as minimizing risk to the patient. We have implemented and compared performance of compression, segmentation and registration algorithms on Clemson\u27s Palmetto supercomputer using dual Nvidia graphics processing units (GPUs) per node and compute unified device architecture (CUDA) programming model. We developed three separate applications that run simultaneously: video acquisition, image processing, and video display. The image processing application allows several algorithms to run simultaneously on different cluster nodes and transfer images through message passing interface (MPI). Our segmentation and registration algorithms resulted in an acceleration factor of around 2 and 8 times respectively. To achieve a higher frame rate, we also resized images and reduced the overall processing time. As a result, using high-speed network to access computing clusters with GPUs to implement these algorithms in parallel will improve surgical procedures by providing real-time medical image processing and laparoscopic data

From Cellular Transport to Synthetic Biomimetic Transport using Carbon Nanotube - Actin Hybrid Assemblies

One of the many interesting materials that have emerged in the field of nanotechnology in the last quarter century is Carbon Nanotube (CNT). CNTs have been explored in a broad range of fields from electronic devices and biosensors, to bioimaging and tissue engineering. However, as stand-alone materials CNTs have limited capabilities in the field of biology and medicine unless they are combined with biological agents. Due to the similarity in diameters, CNTs can be combined with biomolecules such as enzymes, antibodies, antigens, DNA, etc. These hybrid assemblies will combine the properties of the CNTs with the recognition characteristics and functions of the biomolecules.;In our work we utilize one such biomolecule -- actin, which is present in almost all eukaryotic cells and serves as scaffold for molecular motor myosin. The results of the research indicate that actin monomers (G-actins) were able to attach to Multi-Walled Carbon Nanotubes (MWCNTs). The MWCNTs exhibited close to full coverage by the Gactin proteins. Moreover, the G-actins remained functional and were able to polymerize into actin filaments (F-actin) onto the MWCNT scaffolds. Furthermore, the functionality of actin filaments on the surface of the MWCNTs was also investigated. The CNT-Factin hybrid assemblies showed limited movement in synthetic environment. This may be partially due to the inability of the myosin motors to recognize the polarity of the actin filaments, or due to steric hindrance and orientation of actin-based hybrids. The results of our work indicate that these hybrid assemblies can be useful for future biosensor applications with the protein acting as an agent for specific detection

Deep Learning-based Information Fusion Frameworks for Stock Price Movement Prediction

The challenges of modeling behaviour of financial markets, such as its high volatility, poor predictive behaviour, and its non-stationary nature, have continuously attracted attention of the researchers to employ advanced engineering methods. Within the context of financial econometrics, stock market movement prediction is a key and challenging problem. The research works reported in this thesis are motivated by the potentials of Artificial Intelligence (AI) and Machine Learning (ML)-based models, especially Deep Neural Network (DNN) architectures, for stock movement prediction. Considering recent progress in design and implementation of advanced DNN-based models, there has been a surge of interest in their application for predicting stock trends. In particular, the focus of the thesis is on utilization of information fusion to combine Twitter data with extended horizon market historical data for the task of price movement prediction. In this regard, the thesis made a number of contributions, first, the Noisy Deep Stock Movement Prediction Fusion (ND-SMPF) framework is proposed to extract news level temporal information; identify relevant words with highest correlation and effects on the stock trends, and; perform information fusion with historical price data. A real dataset is incorporated to evaluate performance of the proposed ND-SMPF framework. In addition, given that recent COVID-19 pandemic has negatively affected financial econometrics and stock markets across the globe, a unique COVID-19 related PRIce MOvement prediction (\CDATA) dataset is constructed. The objective is to incorporate effects of social media trends related to COVID-19 on stock market price movements. A novel hybrid and parallel DNN-based framework is then designed that integrates different and diversified learning architectures. Referred to as the COVID-19 adopted Hybrid and Parallel deep fusion framework for Stock price Movement Prediction (\SMP), innovative fusion strategies are used to combine scattered social media news related to COVID-19 with historical market data and perform accurate price movement prediction during a pandemic crisis

Towards a Green Information Technology Framework by Meta-Analysis Approach

The rapid depletion of natural resources and growing awareness of the environmental deterioration have made sustainability one of the key elements enabling contemporary businesses to thrive. Among the most crucial sustainable practices is the application of Green IT due to the wide use of IT in various business sectors to enhance the performance of businesses. Green Information Technology (IT) has emerged as a vital IT governance concern to promote environmentally-friendly IT use and ecologically responsible business processes. according to various researches in green information technology, this research aims to design a green information technology using Meta-synthesis method. In order to design and explain a comprehensive model, all factors of green information technology have been identified through systematic literature review using 189 papers and content analysis. Then the importance and priority of each proposed factor was determined using Shannon quantitative method. The results reveal cost reduction, data center layout, employee stewardship and participation are the major factors in green information technology. At the end the research results demonstrate a comprehensive framework for green information technology factors

Unprotected Carbohydrate Conversion to Polyhydroxyalkyl Furans and Dihydrofurans: Improvement, Expansion, and Interruption of the Garcia Gonzalez Reaction via Homogeneous and Heterogeneous Catalysis

Biomass conversion of carbohydrates will lay the foundation for the future of materials, chemicals, and fuels. The Garcia Gonzalez reaction, an undervalued reaction coupling carbon nucleophiles with aldose sugars, can be an integral part of the carbohydrate conversion world, given the high yields, ease of tunability, mild conditions, and ease of setup. The improvement of the homogeneous catalysis of the Garcia Gonzalez reaction, using zirconium chloride as the catalyst, allows for more mild, facile synthesis of polyhydroxyalkyl and C-glycosyl furans. The expansion of the catalysts to a well-defined metal-organic framework, specifically UiO-66, showcases an example of heterogenizing a catalyst for a reaction system, as well as tuning the catalytic and morphological properties. Finally, interruption of the Garcia Gonzalez reaction is displayed by accessing a polyhydroxyalkyl dihydrofuran, rather than the polyhydroxyalkyl furans synthesized in the previous chapters, by using a cheap, recyclable magnesium oxide catalyst.Ph.D

Effect of Liquid Organic Fertilizers and Soil Moisture Status on Some Biological and Physical Properties of Soil

This study was conducted to evaluate the effects of liquid organic fertilizers (LOFs) and soil moisture status on some biological and physical properties of postharvest soil of maize cultivation. For this purpose, a factorial greenhouse experiment was performed based on the completely randomized design with three replications. Treatments consisted of five levels of LOFs (control, vermicompost tea, vermiwash, plant growth-promoting rhizobacteria [PGPR] enriched vermicompost tea and PGPR enriched vermiwash) and three levels of soil moisture status (field capacity [FC], 0.8 FC and 0.6 FC). The results showed LOFs caused an increase of soil biological properties (soil microbial respiration, soil microbial biomass, dehydrogenase activity and the number of aerobic heterotrophic bacteria) and the improvement of soil physical condition. LOFs increased aggregate stability, hydrophobicity and total porosity, while decreased bulk density and soil penetration resistance. Increasing water stress levels reduced soil biological activity and made soil physical properties more unfavorable. In general, LOFs improved soil conditions by enhancing soil physical and biological properties and decreased the negative effects of water stress. In addition, results showed that LOFs enriched with PGPR could be more effective than non-enriched ones