Computer Sciences Commons^™

Antimicrobial And Cytotoxic Properties Of Extracts From Over-Seasoned Worm-Casts Of The Earthworm Hyperiodrilus Africanus Beddard, 1891, Stephen Olugbemiga Owa, David Adeiza Otohinoyi, Theresa Ibibia Edewor-Ikupoyi, Adeolu Adeola Taiwo, Jenifer Akhere Okosun, Yvonne Oluchi Akujobi, Damilola Grace Oyewale, Tomilola Debby Olaolu, Damilare Emmanuel Rotimi, Osarenkhoe Omorefosa Osemwegie, Oluyomi Stephen Adeyemi

Karbala International Journal of Modern Science

⦁ Background: Despite the continuous interest in the search for therapeutic agents, little attention has been given to the medicinal relevance of earthworm casts, with even less interest in over-seasoned worm-casts. Therefore, this study determined the phytochemical, antimicrobial, and cytotoxic properties of over-seasoned worm-casts of the earthworm Hyperiodrilus africanus (Eudrilidae). Methods: The earthworm casts were extracted with n-hexane, ethanol, and water and the crude extracts were evaluated for the presence of chemical constituents and antimicrobial properties. Cytotoxicity was inferred from the antimitotic effects of the extracts on the radicles of germinating seeds of Sorghum bicolor. Results: The chemical constituent determinations …

A Review On The Ethnobotanical, Phytochemistry, And Pharmacological Activities Of Aristolochia Longa L., Oluwafemi Adeleke Ojo, Matthew Iyobhebhe, Bukola Atunwa, Adebola Busola Ojo

Karbala International Journal of Modern Science

Aristolochia longa L. is a plant native to Algeria and Morocco that has been used by the locals to combat different arrays of infections and diseases found among them. This particular plant is well-known for its therapeutic qualities that could be traced back to the presence of many effective phytochemicals that have been extrapolated from the different parts of the plant, like the leaves and roots: flavonoids, saponins, tannins, 4-hydroxybenzoic acid, β-carotenes, limonenes, and palmitic acids. This plant has been identified in different research articles to be able to manage diseases effectively because it possesses some pharmacological attributes such as; …

Applicability Limits Of The End Face Fiber-Optic Gas Concentration Sensor, Based On Fabry-Perot Interferometer, S.M.R.H. Hussein, A.Zh. Sakhabutdinov, O.G. Morozov, V.I. Anfinogentov, J.A. Tunakova, A.R. Shagidullin, A.A. Kuznetsov, K.A. Lipatnikov, A.R. Nasybullin

Karbala International Journal of Modern Science

The mathematical model of the fiber-optic sensor for gas concentration analysis is under study. The sensor is imple-mented as Fabry-Perot interferometer at the end face of the optical fiber by applying a thin polymer film, which permit-tivity depends on the tested gas concentration. It is shown, that a change in the properties of the optical fiber or the at-mosphere permittivity leads mainly to the spectrum contrast changing and does not change the period and the wave-length shift of its comb. The influence of the polymer film thickness, the environment temperature and humidity on the Fabry-Perot spectrum is analyzed. The necessity …

Molecular Docking Reveals Phytoconstituents Of The Methanol Extract From Muntingia Calabura As Promising Α-Glucosidase Inhibitors, Nurlena Andalia, Muhammad N. Salim, Nurdin Saidi, Muhammad Ridhwan, Muhammad Iqhrammullah, Ummu Balqis

Karbala International Journal of Modern Science

Inhibition of α-glucosidase has been used as a management of type 2 diabetes mellitus, where studies are focused on finding more efficacious and safe drugs. Herein, the research aimed to unveil the potential of phytoconstituents contained in methanol extract of Muntingia calabura leaves in inhibiting α-glucosidase through molecular docking simulation. From a systematic search (Scopus), we found 5 eligible articles and identified 28 phytocompounds. Fisetin, pinostrobin, and rhamnetin identified in M. calabura extract were predicted to have good bioavailability. Finally, fisetin was revealed as the most potential α-glucosidase inhibitor candidate with a binding affinity of -7.5 kcal/mol.

Perturbation Modeling For Molecular Design Of Protein Tyrosine Kinase Inhibitors Using Unsupervised Machine Learning, Keerthi Krishnan

Computational and Data Sciences (MS) Theses

The field of computational drug discovery and development has grown, with the aid of new computational tools for novel molecule discovery. In specific, generative deep learning models have excelled as tools to aid in navigating the large space of known molecules and in the creation of new molecules. These models are fed various representations of molecules as inputs and learn to perform a variety of things, such as the optimization of these molecules towards a targeted property. Ultimately, these generative learning models allow us to build bridges between chemical and continuous spaces to understand the compromise between invoking small incremental …

Development Of Graphical Models And Statistical Physics Motivated Approaches To Genomic Investigations, Yashwanth Lagisetty

Dissertations and Theses (Open Access)

Identifying genes involved in disease pathology has been a goal of genomic research since the early days of the field. However, as technology improves and the body of research grows, we are faced with more questions than answers. Among these is the pressing matter of our incomplete understanding of the genetic underpinnings of complex diseases. Many hypotheses offer explanations as to why direct and independent analyses of variants, as done in genome-wide association studies (GWAS), may not fully elucidate disease genetics. These range from pointing out flaws in statistical testing to invoking the complex dynamics of epigenetic processes. In the …

Hyperspectral Image Analysis Of Food For Nutritional Intake, Shirin Nasr Esfahani

UNLV Theses, Dissertations, Professional Papers, and Capstones

The primary object of this dissertation is to investigate the application of hyperspectral technology to accommodate for the growing demand in the automatic dietary assessment applications. Food intake is one of the main factors that contribute to human health. In other words, it is necessary to get information about the amount of nutrition and vitamins that a human body requires through a daily diet. Manual dietary assessments are time-consuming and are also not precise enough, especially when the information is used for the care and treatment of hospitalized patients. Moreover, the data must be analyzed by nutritional experts. Therefore, researchers …

Application In Medicine: Has Artificial Intelligence Stood The Test Of Time, Mir Ibrahim Sajid, Shaheer Ahmed, Usama Waqar, Javeria Tariq, Mohsin Chundrigar, Samira Shabbir Balouch, Sajid Abaidullah

Medical College Documents

Artificial intelligence (AI) has proven time and time again to be a game-changer innovation in every walk of life, including medicine. Introduced by Dr. Gunn in 1976 to accurately diagnose acute abdominal pain and list potential differentials, AI has since come a long way. In particular, AI has been aiding in radiological diagnoses with good sensitivity and specificity by using machine learning algorithms. With the coronavirus disease 2019 pandemic, AI has proven to be more than just a tool to facilitate healthcare workers in decision making and limiting physician-patient contact during the pandemic. It has guided governments and key policymakers …

Toward A Standard Formal Semantic Representation Of The Model Card Report, Muhammad Tuan Amith, Licong Cui, Degui Zhi, Kirk Roberts, Xiaoqian Jiang, Fang Li, Evan Yu, Cui Tao

Faculty, Staff and Student Publications

BACKGROUND: Model card reports aim to provide informative and transparent description of machine learning models to stakeholders. This report document is of interest to the National Institutes of Health's Bridge2AI initiative to address the FAIR challenges with artificial intelligence-based machine learning models for biomedical research. We present our early undertaking in developing an ontology for capturing the conceptual-level information embedded in model card reports.

RESULTS: Sourcing from existing ontologies and developing the core framework, we generated the Model Card Report Ontology. Our development efforts yielded an OWL2-based artifact that represents and formalizes model card report information. The current release of …

Development Of The Implementation Of Iot Monitoring System Based On Node-Red Technology, Anvar Kabulov, Inomjon Yarashov, Salamat Mirzataev

Karakalpak Scientific Journal

This article describes how to design and implement a process for storing environmental information in a database using the Internet of Things. The problems that need to be solved with the help of this IoT system are the growing demand for forecasts in the world, the demand of the world market for a new sustainable method of implementing the digitization environment through the Internet of Things. The design was implemented using Arduino, Node-Red and sensors, selected when choosing a component based on the required parameters and sent to the database for monitoring and processing. A study of previous work and …

Online Privacy Challenges And Their Forensic Solutions, Bandr Fakiha

Journal of the Arab American University مجلة الجامعة العربية الامريكية للبحوث

In the digital age, internet users are exposed to privacy issues online. Few rarely know when someone else is eavesdropping or about to scam them. Companies, governments, and individual internet users are all vulnerable to security breaches due to the challenges of online privacy ranging from trust and hierarchical control to financial losses. As systems advance, people are optimistic that forensic science will provide long-term interventions that surpass the current solutions, including setting stronger passwords and firewall protection. The future of online privacy is changing, and more practical interventions, such as email, malware, mobile, and network forensics, must be integrated, …

Positive Rate-Dependent Action Potential Prolongation By Modulating Potassium Ion Channels, Candido Cabo

Publications and Research

Pharmacological agents that prolong action potential duration (APD) to a larger extent at slow rates than at the fast excitation rates typical of ventricular tachycardia exhibit reverse rate dependence. Reverse rate dependence has been linked to the lack of efficacy of class III agents at preventing arrhythmias because the doses required to have an anti-arrhythmic effect at fast rates may have pro-arrhythmic effects at slow rates due to an excessive APD prolongation. In this report we show that, in computer models of the ventricular action potential, APD prolongation by accelerating phase 2 repolarization (by increasing I_Ks) and decelerating …

Developing A Miniature Smart Boat For Marine Research, Michael Isaac Eirinberg

Computer Engineering

This project examines the development of a smart boat which could serve as a possible marine research apparatus. The smart boat consists of a miniature vessel containing a low-cost microcontroller to live stream a camera feed, GPS telemetry, and compass data through its own WiFi access point. The smart boat also has the potential for autonomous navigation. My project captivated the interest of several members of California Polytechnic State University, San Luis Obispo’s (Cal Poly SLO) Marine Science Department faculty, who proposed a variety of fascinating and valuable smart boat applications.

Weakly-Supervised Tumor Purity Prediction From Frozen H&E Stained Slides, Matthew Brendel, Vanesa Getseva, Majd Al Assaad, Michael Sigouros, Alexandros Sigaras, Troy Kane, Pegah Khosravi, Juan Miguel Mosquera, Olivier Elemento, Iman Hajirasouliha

Publications and Research

Background

Estimating tumor purity is especially important in the age of precision medicine. Purity estimates have been shown to be critical for correction of tumor sequencing results, and higher purity samples allow for more accurate interpretations from next-generation sequencing results. Molecular-based purity estimates using computational approaches require sequencing of tumors, which is both time-consuming and expensive.

Methods

Here we propose an approach, weakly-supervised purity (wsPurity), which can accurately quantify tumor purity within a digitally captured hematoxylin and eosin (H&E) stained histological slide, using several types of cancer from The Cancer Genome Atlas (TCGA) as a proof-of-concept.

Findings

Our model predicts …

One-Stage Blind Source Separation Via A Sparse Autoencoder Framework, Jason Anthony Dabin

Dissertations

Blind source separation (BSS) is the process of recovering individual source transmissions from a received mixture of co-channel signals without a priori knowledge of the channel mixing matrix or transmitted source signals. The received co-channel composite signal is considered to be captured across an antenna array or sensor network and is assumed to contain sparse transmissions, as users are active and inactive aperiodically over time. An unsupervised machine learning approach using an artificial feedforward neural network sparse autoencoder with one hidden layer is formulated for blindly recovering the channel matrix and source activity of co-channel transmissions. The BSS sparse autoencoder …

Integrating Deep Learning And Hydrodynamic Modeling To Improve The Great Lakes Forecast, Pengfei Xue, Aditya Wagh, Gangfeng Ma, Yilin Wang, Yongchao Yang, Tao Liu, Chenfu Huang

Michigan Tech Publications, Part 1

The Laurentian Great Lakes, one of the world’s largest surface freshwater systems, pose a modeling challenge in seasonal forecast and climate projection. While physics-based hydrodynamic modeling is a fundamental approach, improving the forecast accuracy remains critical. In recent years, machine learning (ML) has quickly emerged in geoscience applications, but its application to the Great Lakes hydrodynamic prediction is still in its early stages. This work is the first one to explore a deep learning approach to predicting spatiotemporal distributions of the lake surface temperature (LST) in the Great Lakes. Our study shows that the Long Short-Term Memory (LSTM) neural network, …

The Significance Of Sonic Branding To Strategically Stimulate Consumer Behavior: Content Analysis Of Four Interviews From Jeanna Isham’S “Sound In Marketing” Podcast, Ina Beilina

Student Theses and Dissertations

Purpose:
Sonic branding is not just about composing jingles like McDonald’s “I’m Lovin’ It.” Sonic branding is an industry that strategically designs a cohesive auditory component of a brand’s corporate identity. This paper examines the psychological impact of music and sound on consumer behavior reviewing studies from the past 40 years and investigates the significance of stimulating auditory perception by infusing sound in consumer experience in the modern 2020s.

Design/methodology/approach:
Qualitative content analysis of audio media was used to test two hypotheses. Four archival oral interview recordings from Jeanna Isham’s podcast “Sound in Marketing” featuring the sonic branding experts …

Du Undergraduate Showcase: Research, Scholarship, And Creative Works: Abstracts, Emma Aggeler, Elena Arroway, Daisy T. Booker, Justin Bravo, Kyle Bucholtz, Megan Burnham, Nicole Choi, Spencer Cockerell, Rosie Contino, Jackson Garske, Kaitlyn Glover, Caroline Hamilton, Haley Hartmann, Madalyne Heiken, Colin Holter, Leah Huzjak, Alyssa Jeng, Cole Jernigan, Chad Kashiwa, Adelaide Kerenick, Emily King, Abigail Langeberg, Maddie Leake, Meredith Lemons, Alec Mackay, Greer Mckinley, Ori Miller, Guy Milliman, Katherine Miromonti, Audrey Mitchell, Lauren Moak, Megan Morrell, Gelella Nebiyu, Zdenek Otruba, Toni V. Panzera, Kassidy Patarino, Sneha Patil, Alexandra Penney, Kevin Persky, Caitlin Pham, Gabriela Recinos, Mary Ringgenberg, Chase Routt, Olivia Schneider, Roman Shrestha, Arlo Simmerman, Alec Smith, Tessa Smith, Nhi-Lac Thai, Kyle Thurmann, Casey Tindall, Amelia Trembath, Maria Trubetskaya, Zachary Vangelisti, Peter Vo, Abby Walker, David Winter, Grayden Wolfe, Leah York

DU Undergraduate Research Journal Archive

Abstracts from the DU Undergraduate Showcase.

Editorial Board

Karbala International Journal of Modern Science

No abstract provided.

Simulating Photo-Disintegration Of 137cs Radioactive Waste Using Various Energies Of Gamma Photons, Hassanain H. Alkazzaz, Asia H. Al-Mashhadani, Kamal H. Lateef

Karbala International Journal of Modern Science

In this study, the possibility of using gamma-ray in photo-disintegration method was examined so that it can be used in the remediation of 137Cs radionuclides waste materials by nuclear transmutation to convert long-lived nuclides to other isotopes nuclides, which are shorter half-life (or stable), by different photo-nuclear reaction channels (γ,n), (γ,2n), (γ,p), (γ, a), (γ,d). A simulation code has been written using MATLAB for conducting calculations of reduction and residual. The results showed that gamma-ray fluxes below 1017 [cm-2 s-1] are not adequate to perform effective incinera-tion of 137Cs, and as for gamma flux of 1018 [cm-2 s-1] it showed …

Engineering Of A Multi-Epitope Subunit Vaccine Against Sasrs-Cov-2 Through The Viroinformatic Approach, Aamir Shehzada, Christijogo Sumartono, Jusak Nugraha, Helen Susilowatid, Andi Yasmin Wijayab, Hafiz Ishfaq Ahmad, Wiwiek Tyasningsih, Fedik Abdul Rantam

Karbala International Journal of Modern Science

The COVID-19 outbreak has infected millions of people worldwide, but no vaccine has been discovered to combat it efficiently. This research aims to design a multi-epitope vaccine using highly efficient B- and T-cell epitopes from the SARS-CoV-2 Surabaya isolate through a viroinformatic approach. First, the putative epitopes were linked together to develop tertiary structures and then docked with toll-like receptor 4 (TLR-4) that demonstrated a robust interaction with a low eigenvalue of 4.816138 e-06. Furthermore, the structure's high immunogenic response was observed and successfully cloned into the expression vector pET28a (+). This implies that the designed vaccine can prove effective …

A Machine Learning Based Approach To Detect The Ethereum Fraud Transactions With Limited Attributes, Rabia Musheer Aziz, Mohammed Farhan Baluch, Sarthak Patel, Pavan Kumar

Karbala International Journal of Modern Science

Ethereum smart contracts have recently received new commercial applications and a lot of attention from the scientific community. Ethereum eliminates the requirement for a trusted third party by allowing untrusted parties to expose contract details in computer code. Nonetheless, as online commerce grows, plenty of fraudulent activities, such as money laundering, bribery, and phishing, emerge as major threats to trade security. For correctly recognizing fraudulent transactions, this paper developed a Light Gradient Boosting Machine (LGBM) technique-based model. The modified LGBM model optimized the parameters of Light GBM using the Euclidean distant structured estimation approach. This paper also examines the performance …

A Bi-Level Data Lowering Method To Minimize Transferring Big Data In The Sensors Of Iot Applications, Ali Kadhum M. Al-Qurabat, Ali Kadhum Idrees, Abdallah Makhoul, Chady Abou Jaoude

Karbala International Journal of Modern Science

In the IoT era, the number of devices connected to it continues to grow significantly. This can lead to an increase in the amount of reported data by these IoT devices. The reported data by the Sensor Nodes (SNs) to the Gateway (GW) drives these IoT sensors to consume their energy and storage. These problems can be solved by reducing the amount of data in the source nodes in order to reduce both the amount of energy consumed and the amount of storage required. Energy consumption represents one aspect of the Quality of Service (QoS) in the sensor nodes of …

An Economical Source For Peroxidase: Maize Cobs, Hathama Razooki Hasan, Ali Waleed Al- Ani

Karbala International Journal of Modern Science

According to the current situation of peroxidase (POD), the relevant studies on this enzyme indicated its importance as a tool in clinical biochemistry and different industrial fields. Most of these studies used the fruits and vegetables as source of this enzyme. So that in order to couple the growing requirements for POD with the recent demands for reduc-ing disposal volume by recycling the plant waste, the aim of the present study was to extract POD through management of municipal bio-waste of Iraqi maize species. A simple, green and economical method was used to extract this enzyme. Our results revealed that …

Efficient Removal Of Common Organic Pollutants From Water By Zn-Doped Tio2 Nanoparticles With Different Applications, Khaled Elgendy, Ibrahim Elmehasseb, Saleh Kandil

Karbala International Journal of Modern Science

Water purification via adsorption without energy consumption was considered a green process. Zn-doped TiO2 nanoparticles were fabricated by the Sol-gel method and characterized by different analysis techniques. Zinc doping of TiO2 increases the surface area to 26.7m2g-1 with adsorption results, 75.1%, 71.1%, and 68.2% for methylene blue, ofloxacin, and SLS, respectively. Variable affecting factors on adsorption have been studied. The adsorption behavior fitted with Langmuir and Freundlich equations than Temkin isotherm, indicating the preferred heterogeneous adsorption at equivalent adsorbent sites. The application of nanoparticles in many synthetic specimens of pollutants gave excellent removal results, which exceeded 75% of detoxification.

Synthesis Of Cuo/Zno And Mgo/Zno Core/Shell Nanoparticles With Plasma Jets And Study Of Their Structural And Optical Properties, Raghad S. Mohammed, Kadhim A. Aadim, Khalid A. Ahmed

Karbala International Journal of Modern Science

This paper reports the synthesis of CuO/ZnO and MgO/ZnO core/shell nanoparticles using atmospheric plasma jets. The characterization of the synthesized CuO/ZnO and MgO/ZnO core/shell nanoparticles were confirmed by a series of techniques, including X-ray diffraction (XRD), scanning electron microscopy (SEM), X-ray dispersive spectroscopy (EDS), transmission electron microscopy (TEM), and UV–Vis spectroscopy. The XRD analysis confirmed no other peaks related to the secondary phases for CuO, MgO, or ZnO, indicating the purity of these nanoparticles. Additionally, EDX analysis confirmed the formation of high purity CuO/ZnO and MgO/ZnO core/shell nanoparticles. The surface morphology, which represented the high agglomeration rate, was investigated using …

Numerical Analysis Of A Silicon-Based Electro-Optic Modulator, Mario Alberto García-Ramírez, Orfil González-Reynoso, Everardo Vargas-Rodríguez, Miguel Angel Bello-Jiménez, Abel García-Barrientos

Karbala International Journal of Modern Science

A phase shift electro-optic semiconductor structure that features a Mach-Zehnder Interferometer (MZI) is numerically analyzed. The interferometer structure considers a highly-doped Si-based waveguide that can control the phase shift by varying the refractive index through the carrier concentration while applying a control voltage. To analyze the structure, Kramers-Kronig dispersion relations, the effective index method and the Drude model are implemented within a finite element software. As a result, for an optical waveguide structure with a 9 mm length and 10 V, it is possible to obtain a phase shift by that allows, at the output of the MZI, total interference …

Partial Pseudo-Random Hashing For Transactional Memory Read/Write Data Processing And Validation, G M Sridevi, Ashoka D V, B V Ajay Prakash

Karbala International Journal of Modern Science

Development of a bypass parallel processing block is one of the emerging and interesting research areas in memory read/write application domain. Many Random Number Generation (RNG) techniques have been introduced for processing the data in storage memory. But the limitations include reduced efficiency, increased computational complexity, high area consumption and higher cost. This paper presents a novel dynamic memory register with optimal XOR design based on partial pseudo-random hashing to process transactional memory read/write data. Transfer characteristics of the current are analysed based on the pseudo differential pair for proficient memory utilization. A memory window is then created and adjusted …

A Content-Based File Identification Dataset: Collection, Construction, And Evaluation, Saja Dheyaa Khudhur, Hassan Awheed Jeiad

Karbala International Journal of Modern Science

File-Type Identification (FTI) is one of the essential functions that can be performed by examining the data blocks' magic numbers. However, this examination leads to a challenge when a file is corrupt, or these magic numbers are missing. Content-based analytics is the best way for file type identification when the magic numbers are not available. This paper prepares and presents a content-based dataset for eight common types of files based on twelve features. We designed our dataset to be used for supervised and unsupervised machine learning models. It provides the ability to classify and cluster these types into two levels, …

Nigella Sativa Methanol Extract Inhibits Pc-3 Cell Line Colonization, Induced Apoptosis, And Modulated Lc3-Based Autophagy, Yusuf Toy, Merve Kivrik, Marwa H. Alkhafaji, Aryan M. Faraj, Ibrahim H. Gecibesler, Can A. Ağca

Karbala International Journal of Modern Science

Nigella sativa has various pharmacological properties and has been used throughout history for a variety of reasons. However, there is limited data about the effects of Nigella sativa (NS) on human cancer cells. This study aimed at observing the roles of methanolic extract of N. sativa on apoptosis and autophagy pathway in the Human PC3 (prostate cancer) cell line. The cell viability was checked by MTT assay. Clonogenic assay was performed to demonstrate clonogenicity and Western blot was used to check caspase-3, TIGAR, p53, and LC3 protein expression. The results demonstrated that PC3 cell proliferation was inhibited, caspase-3 and p53 …