Computer Sciences Commons^™

A Systematic Mapping Study On The Risk Factors Leading To Type Ii Diabetes Mellitus, Karar N. J Musafer, Fahrul Zaman Huyop, Mufeed J Ewadh, Eko Supriyanto, Mohammad Rava

Karbala International Journal of Modern Science

Diabetes is one of the most common diseases that has had devastating effects on the general population. It is also among the most popular research trends in modern medicine. Thus, due to the complexity and desirability of this particular affliction, there is a lot of demand towards understanding this disease better, so that it can pave the way towards better solutions in combating diabetes. The aim of this review is to provide a categorization of the risk factors leading to Type II Diabetes. In order to provide a justification for the type of diabetes, an explanation is provided which covers …

Chemical Composition And Antibacterial Activity Of The Essential Oil Of Myrtus Communis Leaves, Hajar El Hartiti, Amine El Mostaphi, Mariam Barrahi, Aouatif Ben Ali, Nabila Chahboun, Rajaa Amiyare, Abdelkader Zarrouk, Brahim Bourkhiss, Mohammed Ouhssine

Karbala International Journal of Modern Science

The aim of this work is to determine the yield of the essential oil of the Myrtus communis leaves, to identify its chemical composition and to evaluate its antibacterial properties. The plant is harvested from Sidi Ahmed Chrif, a region in Ouazzane, Morocco. The extraction of the essential oil was carried out by hydrodistillation in a Clevenger apparatus type. The average yield was 0.7%. The analysis of this oil by Gas Chromatography coupled with Mass Spectrum (GC/MS) allows the identification of 32 compounds. Eucalyptol was the main compound with 42.43%, followed by myrtenyl acetate (21.25%) and α-pinene (19.39%). Myrtle essential …

Hormones Of Maize Crop As Affected By Potassium Fertilization , Water Quality And Ascobin Foliar Application ., Qais Hussain Al-Samak Prof., Fatima Karim Khudair Alasadi

Karbala International Journal of Modern Science

A pot assay on the plastic container of the wire sunshade in the University of Kerbala's Agricultural Division was conducted to research the impact of potassium treatment, the salinity of irrigation water and ascobin sprinkling, just as their connections, on the some plant hormones activities (auxin, gibberellin and abscisic acid) in developing Zea mays crops in a soil with sandy texture during the farming fall period of 2017–2018. The trial was planned as a factorial one with three factors, Potassium adding are 0, 100 and 200 Kg K.ha^–1 . the irrigation water salinity are 1, 3 and 6 ds.m …

Editorial Board

Karbala International Journal of Modern Science

No abstract provided.

Integrated Multiparametric Radiomics And Informatics System For Characterizing Breast Tumor Characteristics With The Oncotypedx Gene Assay, Michael A. Jacobs, Christopher B. Umbricht, Vishwa S. Parekh, Riham H. El Khouli, Leslie Cope, Katarzyna J. Macura, Susan Harvey, Antonio C. Wolff

Radiology Faculty Publications

Optimal use of multiparametric magnetic resonance imaging (mpMRI) can identify key MRI parameters and provide unique tissue signatures defining phenotypes of breast cancer. We have developed and implemented a new machine-learning informatic system, termed Informatics Radiomics Integration System (IRIS) that integrates clinical variables, derived from imaging and electronic medical health records (EHR) with multiparametric radiomics (mpRad) for identifying potential risk of local or systemic recurrence in breast cancer patients. We tested the model in patients (n = 80) who had Estrogen Receptor positive disease and underwent OncotypeDX gene testing, radiomic analysis, and breast mpMRI. The IRIS method was trained …

Feature Selection Via Random Subsets Of Uncorrelated Features, Long Kim Dang

USF Tampa Graduate Theses and Dissertations

The role of feature selection is crucial in many applications. A few of these include computational biology, image classification and risk management. In biology, gene expression micro array data sets have been used extensively in many areas of research. These data sets typically suffer from an important problem: the ratio between the number of features over the number of examples is very high. This problem mainly affects prediction accuracy because it is best to collect more labeled examples than features. A correlation based random subspace ensemble feature selector (CCC_RSM) was proposed to handle this problem [5]. In this approach, first …

Timing Of Maximal Weight Reduction Following Bariatric Surgery: A Study In Chinese Patients, Ting Xu, Chen Wang, Hongwei Zhang, Xiaodong Han, Weijie Liu, Junfeng Han, Haoyong Yu, Jin Chen, Pin Zhang, Jianzhong Di

Computer Science Faculty Publications

Introduction: Bariatric surgery is a well-received treatment for obesity with maximal weight loss at 12–36 months postoperatively. We investigated the effect of early bariatric surgery on weight reduction of Chinese patients in accordance with their preoperation characteristics.

Materials and Methods: Altogether, 409 patients with obesity from a prospective cohort in a single bariatric center were enrolled retrospectively and evaluated for up to 4 years. Measurements obtained included surgery type, duration of diabetic condition, besides the usual body mass index data tuple. Weight reduction was expressed as percent total weight loss (%TWL) and percent excess weight loss (%EWL).

Results: RYGB or …

Functional Morphology Of Gliding Flight Ii. Morphology Follows Predictions Of Gliding Performance, Jonathan Rader, Tyson L. Hedrick, Yanyan He, Lindsay D. Waldrop

Biology, Chemistry, and Environmental Sciences Faculty Articles and Research

The evolution of wing morphology among birds, and its functional consequences, remains an open question, despite much attention. This is in part because the connection between form and function is difficult to test directly. To address this deficit, in prior work we used computational modeling and sensitivity analysis to interrogate the impact of altering wing aspect ratio, camber, and Reynolds number on aerodynamic performance, revealing the performance landscapes that avian evolution has explored. In the present work, we used a dataset of three-dimensionally scanned bird wings coupled with the performance landscapes to test two hypotheses regarding the evolutionary diversification of …

Optimal Control Of Excitable Systems Near Criticality, Kathleen Finlinson, Woodrow L. Shew, Danile B. Larremore, Juan G. Restrepo

Physics Faculty Publications and Presentations

Experiments suggest that the cerebral cortex gains several functional advantages by operating in a dynamical regime near the critical point of a phase transition. However, a long-standing criticism of this hypothesis is that critical dynamics are rather noisy, which might be detrimental to aspects of brain function that require precision. If the cortex does operate near criticality, how might it mitigate the noisy fluctuations? One possibility is that other parts of the brain may act to control the fluctuations and reduce cortical noise. To better understand basic aspects of controlling neural activity fluctuations, here we numerically and analytically study a …

Machine Learning Applications For Drug Repurposing, Hansaim Lim

Dissertations, Theses, and Capstone Projects

The cost of bringing a drug to market is astounding and the failure rate is intimidating. Drug discovery has been of limited success under the conventional reductionist model of one-drug-one-gene-one-disease paradigm, where a single disease-associated gene is identified and a molecular binder to the specific target is subsequently designed. Under the simplistic paradigm of drug discovery, a drug molecule is assumed to interact only with the intended on-target. However, small molecular drugs often interact with multiple targets, and those off-target interactions are not considered under the conventional paradigm. As a result, drug-induced side effects and adverse reactions are often neglected …

Enrichment Of Ontologies Using Machine Learning And Summarization, Hao Liu

Dissertations

Biomedical ontologies are structured knowledge systems in biomedicine. They play a major role in enabling precise communications in support of healthcare applications, e.g., Electronic Healthcare Records (EHR) systems. Biomedical ontologies are used in many different contexts to facilitate information and knowledge management. The most widely used clinical ontology is the SNOMED CT. Placing a new concept into its proper position in an ontology is a fundamental task in its lifecycle of curation and enrichment.

A large biomedical ontology, which typically consists of many tens of thousands of concepts and relationships, can be viewed as a complex network with concepts as …

Convex Relaxations For Particle-Gradient Flow With Applications In Super-Resolution Single-Molecule Localization Microscopy, Hesam Mazidisharfabadi

McKelvey School of Engineering Graduate Student Theses & Dissertations

Single-molecule localization microscopy (SMLM) techniques have become advanced bioanalytical tools by quantifying the positions and orientations of molecules in space and time at the nanoscale. With the noisy and heterogeneous nature of SMLM datasets in mind, we discuss leveraging particle-gradient flow 1) for quantifying the accuracy of localization algorithms with and without ground truth and 2) as a basis for novel, model-driven localization algorithms with empirically robust performance. Using experimental data, we demonstrate that overlapping images of molecules, a typical consequence of densely packed biological structures, cause biases in position estimates and reconstruction artifacts. To minimize such biases, we develop …

Snow-Albedo Feedback In Northern Alaska: How Vegetation Influences Snowmelt, Lucas C. Reckhaus

Theses and Dissertations

This paper investigates how the snow-albedo feedback mechanism of the arctic is changing in response to rising climate temperatures. Specifically, the interplay of vegetation and snowmelt, and how these two variables can be correlated. This has the potential to refine climate modelling of the spring transition season. Research was conducted at the ecoregion scale in northern Alaska from 2000 to 2020. Each ecoregion is defined by distinct topographic and ecological conditions, allowing for meaningful contrast between the patterns of spring albedo transition across surface conditions and vegetation types. The five most northerly ecoregions of Alaska are chosen as they encompass …

Functional Morphology Of Gliding Flight I. Modeling Reveals Distinct Performance Landscapes Based On Soaring Strategies, Lindsay D. Waldrop, Yanyan He, Tyson L. Hedrick, Jonathan Rader

Biology, Chemistry, and Environmental Sciences Faculty Articles and Research

The physics of flight influences the morphology of bird wings through natural selection on flight performance. The connection between wing morphology and performance is unclear due to the complex relationships between various parameters of flight. In order to better understand this connection, we present a holistic analysis of gliding flight that preserves complex relationships between parameters. We use a computational model of gliding flight, along with analysis by uncertainty quantification, to 1) create performance landscapes of gliding based on output metrics (maximum lift-to-drag ratio, minimum gliding angle, minimum sinking speed, lift coefficient at minimum sinking speed); and 2) predict what …

An Investigation Into Multi-View Error Correcting Output Code Classifiers Applied To Organ Tissue Classification, Daniel Alvarez

UNLV Theses, Dissertations, Professional Papers, and Capstones

Large amounts of data is being generated constantly each day, so much data that it is difficult to find patterns in order to predict outcomes and make decisions for both humans and machines alike. It would be useful if this data could be simplified using machine learning techniques. For example, biological cell identity is dependent on many factors tied to genetic processes. Such factors include proteins, gene transcription, and gene methylation. Each of these factors are highly complex mechanism with immense amounts of data. Simplifying these can then be helpful in finding patterns in them. Error-Correcting Output Codes (ECOC) does …

Hypergraph Analysis Of Structure Models, Cliff A. Joslyn, Teresa D. Schmidt, Martin Zwick

Complex Systems Faculty Publications and Presentations

Theoretical discussion on the analysis of hypergraph networks; application of analysis methods to hypergraph networks derived by applying Reconstructability Analysis to health care data (the PhD dissertation work of Teresa Schmidt).

Allosteric Regulation At The Crossroads Of New Technologies: Multiscale Modeling, Networks, And Machine Learning, Gennady M. Verkhivker, Steve Agajanian, Guang Hu, Peng Tao

Mathematics, Physics, and Computer Science Faculty Articles and Research

Allosteric regulation is a common mechanism employed by complex biomolecular systems for regulation of activity and adaptability in the cellular environment, serving as an effective molecular tool for cellular communication. As an intrinsic but elusive property, allostery is a ubiquitous phenomenon where binding or disturbing of a distal site in a protein can functionally control its activity and is considered as the “second secret of life.” The fundamental biological importance and complexity of these processes require a multi-faceted platform of synergistically integrated approaches for prediction and characterization of allosteric functional states, atomistic reconstruction of allosteric regulatory mechanisms and discovery of …

Β-Amyloid And Tau Drive Early Alzheimer's Disease Decline While Glucose Hypometabolism Drives Late Decline, Tyler C. Hammond, Xin Xing, Chris Wang, David Ma, Kwangsik Nho, Paul K. Crane, Fanny Elahi, David A. Ziegler, Gongbo Liang, Qiang Cheng, Lucille M. Yanckello, Nathan Jacobs, Ai-Ling Lin

Sanders-Brown Center on Aging Faculty Publications

Clinical trials focusing on therapeutic candidates that modify β-amyloid (Aβ) have repeatedly failed to treat Alzheimer’s disease (AD), suggesting that Aβ may not be the optimal target for treating AD. The evaluation of Aβ, tau, and neurodegenerative (A/T/N) biomarkers has been proposed for classifying AD. However, it remains unclear whether disturbances in each arm of the A/T/N framework contribute equally throughout the progression of AD. Here, using the random forest machine learning method to analyze participants in the Alzheimer’s Disease Neuroimaging Initiative dataset, we show that A/T/N biomarkers show varying importance in predicting AD development, with elevated biomarkers of Aβ …

Nobiletin Affects Circadian Rhythms And Oncogenic Characteristics In A Cell-Dependent Manner, Sujeewa S. Lellupitiyage Don, Kelly L. Robertson, Hui-Hsien Lin, Caroline Labriola, Mary E. Harrington, Stephanie R. Taylor, Michelle E. Farkas

Psychology: Faculty Publications

The natural product nobiletin is a small molecule, widely studied with regard to its therapeutic effects, including in cancer cell lines and tumors. Recently, nobiletin has also been shown to affect circadian rhythms via their enhancement, resulting in protection against metabolic syndrome. We hypothesized that nobiletin’s anti-oncogenic effects, such as prevention of cell migration and formation of anchorage independent colonies, are correspondingly accompanied by modulation of circadian rhythms. Concurrently, we wished to determine whether the circadian and anti-oncogenic effects of nobiletin differed across cancer cell lines. In this study, we assessed nobiletin’s circadian and therapeutic characteristics to ascertain whether these …

Estimating Gene Expression From Dna Methylation And Copy Number Variation: A Deep Learning Regression Model For Multi-Omics Integration, Dibyendu Bikash Seal, Vivek Das, Saptarsi Goswami, Rajat K. De

ISI Best Publications

Gene expression analysis plays a significant role for providing molecular insights in cancer. Various genetic and epigenetic factors (being dealt under multi-omics) affect gene expression giving rise to cancer phenotypes. A recent growth in understanding of multi-omics seems to provide a resource for integration in interdisciplinary biology since they altogether can draw the comprehensive picture of an organism's developmental and disease biology in cancers. Such large scale multi-omics data can be obtained from public consortium like The Cancer Genome Atlas (TCGA) and several other platforms. Integrating these multi-omics data from varied platforms is still challenging due to high noise and …

Device–To-Device Association Algorithm For Optimal Neighbour Selection And Channel Sharing In 5g Cellular Networks, Chiza Christophe, Omar Hamad, Libe Massawe, Abdi Abdalla

Tanzania Journal of Science

The integration of device-to-device (D2D) communication in 5G cellular networks has generated the possibility of multiple transmission modes in a single cell. This has motivated scholars to investigate different mode selection and D2D association algorithms that guarantee the selection of proper transmission mode. However, the complexity of algorithms and tractability of devices in the cell are still remarkably challenging. This paper, therefore, presents a utility based D2D association algorithm that ensures optimal neighbour selection by using numerical linear algebra to minimize computational complexity. Simulation results show that the minimum utility based D2D association increases the expected values of attached devices …

Introduction To The R-Package: Usdampr, Elliott James Dennis, Bowen Chen

Extension Farm and Ranch Management News

Why the Need for the Package? In the 1990’s, concern over growing packer concentration and a hog industry market shock resulted in discontent among producers and packers. As a result, the United States Congress passed the Livestock Mandatory Reporting Act of 1999 (1999 Act) [Pub. L. 106-78, Title IX] which is required to be reauthorized every five years. See here for a full history of the Livestock Mandatory Reporting Background.

Market reports were publicly issued in the form of .txt files with varying frequency from April 2000 to April 2020. Current and historical data were also housed in a USDA-AMS …

Synthesis, Characterisation And Biological Evaluation Of Tyramine Derived Schiff Base Ligand And Its Transition Metal(Ii) Complexes, Abdul Khader Jailani, N.S.K. Gowthaman, Mookkandi Palsamy Kesavan

Karbala International Journal of Modern Science

In this study, a new tyramine derived Schiff base ligand (L) (L=1,3-phenylene-bis-4-aminoantipyrinyl-4-aminoethylphenol) and its derived transition metal(II) complexes [Cu(L)Cl₂](1), [Ni(L)Cl₂](2), [Co(L)Cl₂] (3) and [Zn(L)Cl₂] (4) have been synthesized and well characterized by the way of different spectroscopic and analytical techniques. Analytical and spectroscopic studies result suggests that metal(II) complexes more probably have octahedral geometry. DNA binding tendency of L and metal(II) complexes 1-4 have been assessed by probing their ability to bind with Calf Thymus DNA (CT-DNA) via electronic absorption and cyclic voltammetry titration methods. The results clearly reveal that the metal(II) …

Evaluation Of Structure And Properties Of Various Sol–Gel Nanocoatings On Biomedical Titanium Surface, Mohsin Talib Mohammed, Sarah Mohammed Hussein

Karbala International Journal of Modern Science

This study deals with the preparation and characterization of different bioceramic nanofilms formed on the surface of new metastable β-titanium (Ti) alloy. The films of pure TiO₂, pure HA, TiO₂/HA bilayer and HA/TiO₂ composite were coated successfully on Ti surface by sol-gel using spray pyrolysis deposition technique. The surface characteristics of coated substrates, such as thickness, topography, morphology, phase transformations and wear behavior, were evaluated and compared to uncoated substrate. The results showed that the sol-gel is a promising technique to create biocoatings on Ti surface with outstanding structure and properties for biomedical applications.

On The Dynamic Behaviour Of Automobile Pulleys Under Cyclic Loading, Haval Kamal Asker, Thaker Saleh Dawood

Karbala International Journal of Modern Science

This paper investigates the dynamic characteristics of pulley systems with different numbers of bolt holes. Models with four, six and eight bolt holes were chosen for the pulley. Three sets of cyclic pressure were applied to the pulley system to resemble the different running revolutions of an engine. The study investigates the effect of the number of holes on the system’s stiffness and natural frequency. Finite element models were used to simulate the obtained deformations, stresses and frequency response function (FRF) for pulley models comprising four, six and eight bolt holes under different cyclic pressures. The results show that the …

Optically Thick Radiating Free Convective Mhd Nanofluid Flow Over An Exponentially Accelerated Plate, D.P. Bhatta, S.R. Mishra, J.K. Dash

Karbala International Journal of Modern Science

The present analysis investigates an unsteady conducting water-based nanofluid embedding with porous medium over an exponentially accelerated vertical plate. The plate is accelerated with moving ramped temperature. However, water is treated as the base fluid with Copper (Cu) and Titanium Oxide (TiO₂) as nanoparticles. Effects of thermal radiation, heat source, and radiation absorption are taken care of in the energy equation which may enhance the heat transfer properties of nanofluid. The crux of the investigation is to find the closed-form solution of nonlinear coupled partial differential equations. Laplace Transform technique is employed to solve these equations. The influence …

A Support Vector Machine-Based Prediction Model For Electrochemical Machining Process, Subham Agarwal Mr., Shruti Sudhakar Dandge Ms., Shankar Chakraborty Prof.

Karbala International Journal of Modern Science

Manufacturing of quality products is one of the core measures to address competitiveness in industries. Hence, it is always necessary to accomplish quality prediction at early stages of a manufacturing process to attain high quality products at the minimum possible cost. To achieve this goal, the past researchers have developed and investigated the applications of different intelligent techniques for their effective deployment at various stages of manufacturing processes. In this paper, support vector machine (SVM), a supervised learning system based on a novel artificial intelligence paradigm, is employed for prediction of three responses, like material removal rate, surface roughness and …

Influence Of Carbon Fibres On Strain Sensing And Structural Properties Of Rc Beams Without Stirrups, Arvind Kumar Cholker, Manzoor Ahmad Tantray

Karbala International Journal of Modern Science

In present study, effect of micro carbon fibres on strain sensing property and structural behavior of the reinforced concrete (RC) beams in absence of stirrups was experimentally investigated. A total of three RC beams of dimensions, 125 mm width, 350 mm height and 1500 mm long were manufactured without stirrups. All the three beams had different longitudinal reinforcement ratios (0.9%, 1.43% and 1.03 %) and uniform strength of concrete of 36.5 MPa. All the beams had carbon fibre based concrete (CFBC) at top and bottom surface in mid span for a length of 350mm and depth of 78 mm. All …

Approximating Fixed Points In Modular Spaces, Salwa Salman Abed, Meena Fouad Abduljabbar

Karbala International Journal of Modern Science

A generic two theorems for the two step iterative sequence of multivalued mappings are proved in a complete convex real modular space, and then cite some corollaries that are special cases of these theorems.

Editorial Board

Karbala International Journal of Modern Science

No abstract provided.