Computer Sciences Commons^™

Neighborhoods And Partial Sums Of A New Class Of Meromorphic Multivalent Functions Defined By Fractional Calculus, Aqeel Ketab Al-Khafaji, Waggas Galib Atshan, Salwa Salman Abed

Karbala International Journal of Modern Science

In this paper, we introduce and study a new class A^* (λ,μ,ν,η,p,ζ,τ) of meromorphic multivalent functions defined by fractional calculus operator of the punctured unit disc U^*. On this class we obtain several results like, coefficient inequality, modified Hadamard product, (N,δ)- neighborhood, partial sums, convex linear combination and integral operator.

Biomedical Applications Of Chasmanthera Dependens Stem Extract Mediated Silver Nanoparticles As Antimicrobial, Antioxidant, Anticoagulant, Thrombolytic, And Larvicidal Agents, Daniel Ayandiran Aina, Oluwafayoke Owolo, Agbaje Lateef, Folasade O. Aina, Abbas Saeed Hakeem, Morenike Adeoye-Isijola, Victor Okon, Tesleem B. Asafa, Joseph Adetunji Elegbede, Olumide D. Olukanni, Isaac Adediji

Karbala International Journal of Modern Science

The stem extract of Chasmanthera dependens was used in the biofabrication of silver nanoparticles (AgNPs) in this study. The AgNPs was characterised using UV-visible spectroscopy, Field Emission Scanning Electron Microscope (FESEM), EDX, and the Fourier Transform Infrared Spectroscopy (FTIR). Antibacterial, antioxidant, anticoagulant, thrombolytic and larvicidal activities of the biosynthesised nanoparticles were carried out. There was a peak at 418 nm with a strong silver peak observed around 2.7KeV when the EDX analysis was carried out. The FESEM showed a large number of cubically shaped nanoparticles with sizes ranging from 24.53 to 92.38 nm. CDE-AgNPs was effective against Klebsiella pneumoniae at …

Editorial Board

Karbala International Journal of Modern Science

No abstract provided.

"Flagella Base Model" And "Flagellin Monomer", Brandon Lasalle, Rebecca Roston

3-D Printed Model Structural Files

"Flagella Base Model" and "Flagellin monomer"

Description: This is a teaching model of the proteins that make a bacterial flagella. All models are depicted in space-fill. The Flagellin monomer and the Flagella base can slot together to show protein quaternary structure and filamentous protein assembly.

Printable models are already uploaded to Shapeways.com in the MacroMolecules shop under the names "Flagella Base Model" and "Flagellin monomer".

This model has been printed successfully using these parameters on Shapeways’ laser sintering printer in the following material: Processed Versatile Plastic (Strong & Flexible Plastic).

Model designer: Brandon Lasalle Authors: Brandon Lasalle and Rebecca Roston …

Integration Of Random Forest Classifiers And Deep Convolutional Neural Networks For Classification And Biomolecular Modeling Of Cancer Driver Mutations, Steve Agajanian, Odeyemi Oluyemi, Gennady M. Verkhivker

Mathematics, Physics, and Computer Science Faculty Articles and Research

Development of machine learning solutions for prediction of functional and clinical significance of cancer driver genes and mutations are paramount in modern biomedical research and have gained a significant momentum in a recent decade. In this work, we integrate different machine learning approaches, including tree based methods, random forest and gradient boosted tree (GBT) classifiers along with deep convolutional neural networks (CNN) for prediction of cancer driver mutations in the genomic datasets. The feasibility of CNN in using raw nucleotide sequences for classification of cancer driver mutations was initially explored by employing label encoding, one hot encoding, and embedding to …

High-Performance Computing Frameworks For Large-Scale Genome Assembly, Sayan Goswami

LSU Doctoral Dissertations

Genome sequencing technology has witnessed tremendous progress in terms of throughput and cost per base pair, resulting in an explosion in the size of data. Typical de Bruijn graph-based assembly tools demand a lot of processing power and memory and cannot assemble big datasets unless running on a scaled-up server with terabytes of RAMs or scaled-out cluster with several dozens of nodes. In the first part of this work, we present a distributed next-generation sequence (NGS) assembler called Lazer, that achieves both scalability and memory efficiency by using partitioned de Bruijn graphs. By enhancing the memory-to-disk swapping and reducing the …

Model-Based Deep Autoencoders For Characterizing Discrete Data With Application To Genomic Data Analysis, Tian Tian

Dissertations

Deep learning techniques have achieved tremendous successes in a wide range of real applications in recent years. For dimension reduction, deep neural networks (DNNs) provide a natural choice to parameterize a non-linear transforming function that maps the original high dimensional data to a lower dimensional latent space. Autoencoder is a kind of DNNs used to learn efficient feature representation in an unsupervised manner. Deep autoencoder has been widely explored and applied to analysis of continuous data, while it is understudied for characterizing discrete data. This dissertation focuses on developing model-based deep autoencoders for modeling discrete data. A motivating example of …

Is The Selective Tuning Model Of Visual Attention Still Relevant?, John K. Tsotsos

MODVIS Workshop

No abstract provided.

Simplicity Diffexpress: A Bespoke Cloud-Based Interface For Rna-Seq Differential Expression Modeling And Analysis, Cintia C. Palu, Marcelo Ribeiro-Alves, Yanxin Wu, Brendan Lawlor, Pavel V. Baranov, Brian Kelly, Paul Walsh

Department of Computer Science Publications

One of the key challenges for transcriptomics-based research is not only the processing of large data but also modeling the complexity of features that are sources of variation across samples, which is required for an accurate statistical analysis. Therefore, our goal is to foster access for wet lab researchers to bioinformatics tools, in order to enhance their ability to explore biological aspects and validate hypotheses with robust analysis. In this context, user-friendly interfaces can enable researchers to apply computational biology methods without requiring bioinformatics expertise. Such bespoke platforms can improve the quality of the findings by allowing the researcher to …

Identification And Classification Of Poultry Eggs: A Case Study Utilizing Computer Vision And Machine Learning, Jeremy Lubich, Kyle Thomas, Daniel W. Engels

SMU Data Science Review

We developed a method to identify, count, and classify chickens and eggs inside nesting boxes of a chicken coop. Utilizing an IoT AWS Deep Lens Camera for data capture and inferences, we trained and deployed a custom single-shot multibox (SSD) object detection and classification model. This allows us to monitor a complex environment with multiple chickens and eggs moving and appearing simultaneously within the video frames. The models can label video frames with classifications for 8 breeds of chickens and/or 4 colors of eggs, with 98% accuracy on chickens or eggs alone and 82.5% accuracy while detecting both types of …

Draft Genome Sequences Of Three Monokaryotic Isolates Of The White-Rot Basidiomycete Fungus Dichomitus Squalens, Sara Casado López, Mao Peng, Paul Daly, Bill Andreopoulos, Jasmyn Pangilinan, Anna Lipzen, Robert Riley, Steven Ahrendt, Vivian Ng, Kerrie Barry, Chris Daum, Igor Grigoriev, Kristiina Hildén, Miia Mäkelä, Ronald De Vries

Faculty Publications, Computer Science

Here, we report the draft genome sequences of three isolates of the wood-decaying white-rot basidiomycete fungus Dichomitus squalens. The genomes of these monokaryons were sequenced to provide more information on the intraspecies genomic diversity of this fungus and were compared to the previously sequenced genome of D. squalens LYAD-421 SS1.

A Machine Learning Technology For Rapid Detection Of Carbon Nanotubes/Dna Hybridization In Biosensor Healthcare Applications, Steven K. Ang

Master's Theses

In molecular biology, the term “DNA hybridization” generally refers to the process of forming a double stranded nucleic acid from joining two complementary strands of DNA. The degree of genetic similarity of the DNA resulting from hybridization can be detected ei ther by using the chemical characteristics of DNA samples or by utilizing reliable biosensors which transform the chemical characteristics into a source of electrical measurements. In past research about such sensors, known as DNA Hybridization Detection Systems, the thermal and electrical characteristics of carbon nanotubes are utilized to detect whether hybridization takes place or not. However, human interpretation of …

Designing Computational Biology Workflows With Perl - Part 1 & 2, Esma Yildirim

Open Educational Resources

This manual guides the instructor to combine the partial files of the virtual machine image and construct sequencer.ova file. It is accompanied by the partial files of the virtual machine image.

Designing Computational Biology Workflows With Perl - Part 2, Esma Yildirim

Open Educational Resources

This material briefly reintroduces the DNA double Helix structure, explains SNP and INDEL mutations in genes and describes FASTA, FASTQ, BAM and VCF file formats. It also explains the index creation, alignment, sorting, marking duplicates and variant calling steps of a simple preprocessing workflow and how to write a Perl script to automate the execution of these steps on a Virtual Machine Image.

Designing Computational Biology Workflows With Perl - Part 1, Esma Yildirim

Open Educational Resources

This material introduces Linux File System structures and demonstrates how to use commands to communicate with the operating system through a Terminal program. Basic program structures and system() function of Perl are discussed. A brief introduction to gene-sequencing terminology and file formats are given.

Designing Computational Biology Workflows With Perl - Part 1, Esma Yildirim

Open Educational Resources

This material introduces the AWS console interface, describes how to create an instance on AWS with the VMI provided, connect to that machine instance using the SSH protocol. Once connected, it requires the students to write a script to enter the data folder, which includes gene-sequencing input files and print the first five line of each file remotely. The same exercise can be applied if the VMI is installed on a local machine using virtualization software (e.g. Oracle VirtualBox). In this case, the Terminal program of the VMI can be used to do the exercise.

Designing Computational Biology Workflows With Perl - Part 2, Esma Yildirim

Open Educational Resources

This material introduces the AWS console interface, describes how to create an instance on AWS with the VMI provided and connect to that machine instance using the SSH protocol. Once connected, it requires the students to write a script to automate the tasks to create VCF files from two different sample genomes belonging to E.coli microorganisms by using the FASTA and FASTQ files in the input folder of the virtual machine. The same exercise can be applied if the VMI is installed on a local machine using virtualization software (e.g. Oracle VirtualBox). In this case, the Terminal program of the …

An Artificial Sweating System For Sweat Sensor Testing Applications, Andrew Brueck, Kyle Bates, Trent Wood, William House, Zachary Martinez, Shannon Peters, Blain Root, Kumar Yelamarthi, Tolga Kaya

School of Computer Science & Engineering Faculty Publications

This research proposes a completely automated, computer-controlled fluid mixing and dispensing system, which is suitable for testing sweat sensing devices, as an alternative to requiring human trials during the development phase of a sweat sensor device. An arm mold was designed and implemented with dragon skin and pores to simulate sweating action. The relay controlled mixing tanks allow for the different concentration of fluid solutions at various rates of fluid dispensing through pores. The onboard single board computer controls a dozen electronic relays and it switches and presents an easy to use graphical user interface to allow end users to …

Gogo: An Improved Algorithm To Measure The Semantic Similarity Between Gene Ontology Terms, Chenguang Zhao

Master's Theses

Measuring the semantic similarity between Gene Ontology (GO) terms is an essential step in functional bioinformatics research. We implemented a software named GOGO for calculating the semantic similarity between GO terms. GOGO has the advantages of both information-content-based and hybrid methods, such as Resnik’s and Wang’s methods. Moreover, GOGO is relatively fast and does not need to calculate information content (IC) from a large gene annotation corpus but still has the advantage of using IC. This is achieved by considering the number of children nodes in the GO directed acyclic graphs when calculating the semantic contribution of an ancestor node …

A Data-Driven Approach For Detecting Stress In Plants Using Hyperspectral Imagery, Suraj Gampa

School of Computing: Dissertations, Theses, and Student Research

A phenotype is an observable characteristic of an individual and is a function of its genotype and its growth environment. Individuals with different genotypes are impacted differently by exposure to the same environment. Therefore, phenotypes are often used to understand morphological and physiological changes in plants as a function of genotype and biotic and abiotic stress conditions. Phenotypes that measure the level of stress can help mitigate the adverse impacts on the growth cycle of the plant. Image-based plant phenotyping has the potential for early stress detection by means of computing responsive phenotypes in a non-intrusive manner. A large number …

Discrete-Position Solar Tracking For Photovoltaic System, Shengnan Hong, Zheng Fu, Richard E. Stamper

Rose-Hulman Undergraduate Research Publications

The purpose of this research is to design a new tracking system for solar panels using the idea of discrete-position tracking. Compared with the traditional fixed solar panel, discrete-position trackers have a higher gain of harvesting solar radiation with smaller misalignment angles. Also, since we are trying to design the a passive tracker with solely mechanical structure to do the kinetics, a discrete-position tracker can decrease the cost of the maintenance to a huge extent in contrast to both one-axis and two-axis continuous tracking systems. The majority of the cost of maintaining a continuous tracker is the motor or hydraulic …

Fys: Ethics And Technology (Phil 07/Cpsc 15) Syllabus, Ameet Soni, Krista Karbowski Thomason

Digital Humanities Curricular Development

There has been an accelerated shift in the influence of computing technology and the use of algorithms in our daily lives. With this technology comes serious ethical questions. Philosophers are often well-equipped to wrestle with ethical questions, but less well-equipped to wrestle with questions of technology itself. Computer scientists are well-equipped to deal with the problems and challenges of technology, but less well-equipped to deal with the ethical problems and challenges that technology can pose. In this co-taught course, we bring together the two fields to address ethical questions involving social media, data mining, self-driving cars, artificial intelligence, and other …

Lab Practicum For Bias In Algorithms, Ameet Soni, Krista Karbowski Thomason

Digital Humanities Curricular Development

This is a course assignment to demonstrate potential biases encoded in algorithms (this can be linked more specifically to natural language processing, machine learning, or artificial intelligence) using the Word Embedding Association Test. In lab, students will work with programs that demonstrate the usefulness of word embedding algorithms in finding relationships between words. Then, students will use an implementation of the algorithm in "Semantics derived automatically from language corpora contain human-like biases" by Caliskan et al. to detect gender and racial bias encoded in word embeddings. The assignment has students design and run an experiment using the WEAT algorithm to …

Highly Accurate Fragment Library For Protein Fold Recognition, Wessam Elhefnawy

Computer Science Theses & Dissertations

Proteins play a crucial role in living organisms as they perform many vital tasks in every living cell. Knowledge of protein folding has a deep impact on understanding the heterogeneity and molecular functions of proteins. Such information leads to crucial advances in drug design and disease understanding. Fold recognition is a key step in the protein structure discovery process, especially when traditional computational methods fail to yield convincing structural homologies. In this work, we present a new protein fold recognition approach using machine learning and data mining methodologies.

First, we identify a protein structural fragment library (Frag-K) composed of a …

Computational Contributions To The Automation Of Agriculture, Micah Nagel

Senior Honors Theses

The purpose of this paper is to explore ways that computational advancements have enabled the complete automation of agriculture from start to finish. With a major need for agricultural advancements because of food and water shortages, some farmers have begun creating their own solutions to these problems. Primarily explored in this paper, however, are current research topics in the automation of agriculture. Digital agriculture is surveyed, focusing on ways that data collection can be beneficial. Additionally, self-driving technology is explored with emphasis on farming applications. Machine vision technology is also detailed, with specific application to weed management and harvesting of …

Modeling And Economic Analysis Of A Crop–Livestock Production System Incorporating Cereal Rye As A Forage, Eric R. Coufal

Department of Agricultural Economics: Dissertations, Theses, and Student Research

This thesis consists of two chapters using agent-based modeling for a crop-livestock production system incorporating human labor. The first chapter examines the principles used to develop a fundamental simulation pertaining to grazing cereal rye (Secale cereal L.) with calves. Within the software guidelines, the base model has the ability to capture diverse system interactions between livestock/plants and land management with human labor efficiency. AnyLogic incorporates agent-based modeling while combining with discrete event modeling and system dynamics. The purpose of the model was to find the economic returns of grazing cover crops relative to the area of Mead, Nebraska. In …

Hinge Region In Dna Packaging Terminase Pul15 Of Herpes Simplex Virus: A Potential Allosteric Target For Antiviral Drugs, Lana Faisal Thaljeh

Honors Capstones

No abstract provided.

Mosquito Image Classification Using Convolutional Neural Networks, Sumanth Vissamsetty

LSU Master's Theses

Human life has always been affected by insects, especially mosquitoes, since it's early beginnings. This pesky insect acts as a vector that transmit pathogens through feeding on our blood, spreading life-threatening diseases like Zika Virus, Malaria, Dengue fever, Chikungunya and more. It is important to prevent these mosquitoes from harming humans and one way to do so is to control the mosquito population, or mosquito abatement as it is commonly known. It is important to note that not all mosquitoes are the same and each of them live, reproduce and attack in their own unique way. Hence it is crucial …

Editorial Board

Karbala International Journal of Modern Science

No abstract provided.

Data Analytics Pipeline For Rna Structure Analysis Via Shape, Quinn Nelson

UNO Student Research and Creative Activity Fair

Coxsackievirus B3 (CVB3) is a cardiovirulent enterovirus from the family Picornaviridae. The RNA genome houses an internal ribosome entry site (IRES) in the 5’ untranslated region (5’UTR) that enables cap-independent translation. Ample evidence suggests that the structure of the 5’UTR is a critical element for virulence. We probe RNA structure in solution using base-specific modifying agents such as dimethyl sulfate as well as backbone targeting agents such as N-methylisatoic anhydride used in Selective 2’-Hydroxyl Acylation Analyzed by Primer Extension (SHAPE). We have developed a pipeline that merges and evaluates base-specific and SHAPE data together with statistical analyses that provides confidence …