TTU Published Journals @ Volpe Library
Not a member yet
971 research outputs found
Sort by
Analyzing the mechanical properties along the length of human Achilles tendon
No full textThe literature shows there is no valid procedure to measure the tensile properties in different regions along the length of human tendons. The slippery surfaces and non-homogeneous properties of tendons reduce the probability of success when using traditional methods. So, there is a need to implement an experimental technique that ensures accurate measurement of the mechanical properties of human tissue. The development of new technologies allows us to face problems with new approaches. Computer vision is a trending topic in the development of new technology, one of its branches is digital image correlation (DIC). DIC is a non-contact technique used for tracking pixels along a group of sequential images, and, when combined with tensile testing, can be used to track sample deformation and strain at discrete points in space. This work investigates mechanical testing of Achilles tendons using digital image correlation (DIC) and custom-designed 3D printed clamps. The advantage of DIC is that it analyzes the deformation of the tendon throughout the complete sample, allowing us to quantify the mechanical properties in different regions within the tendon. These results can be used in the future to aid in the design and material selection of prosthetic tendons for people suffering from injury or disease
An Efficient Method of Analyzing Conservative Reversible Logic Gates and Circuits
No full textComputers, which have become a ubiquitous staple of modern society, consume nearly 10% of all the energy produced worldwide. While computing implementation technology has been made more energy efficient over the years, the energy required to operate a gate logically has become an increasingly large proportion of the total energy required. A systematic improvement of this power use would result in significant power savings, which would grow even more appreciable as overall efficiency improves. One method for achieving these power savings would be the use of conservative reversible logic (CRL) gates for system design. However, to date, only a few designs using these types of gates have been developed. One of the reasons for this sporadic development is due to the lack of an efficient method of analyzing CRL gates and circuits. This work describes an accurate and efficient method for analyzing the outputs of CRL gates and circuits of any size using a modified Karnaugh Map (K-Map). The full analysis of several CRL gates and circuits are presented, along with an efficiency comparison to conventional analysis methods
The Electrical Potential in an Irregular Rectangular Domain: An Area-Averaging Approach
No full textElectrostatic potentials are critically important for applications such as electrophoretic separation, microfluidics, and other electrokinetic-driven technology. As in other transport processes, the microscopic electrostatic equation and its boundary conditions depend upon the geometry of the domain, i.e. pore or capillary of the, for example, hydrogel used in this application. Since these materials display a complicated morphology of the pore network, "irregular domains" play an important role in capturing a realistic description of the electrostatic potential. Studies have shown that generally, diverging channels, a form of irregular channel, give better separation resolutions compared to regular channels. In this project, an area-averaging approach coupled with its closure condition are used for the analysis of the electrostatic potential in a diverging channel of rectangular geometry. Both area-averaged values of the electrostatic potential and its deviation are systematically determined and used to obtain the solution, i.e., the "local" or microscopic value of the potential without using other more mathematically involved techniques such as separation of variables. The presentation will discuss details about the up scaling of the microscopic electrostatic equation to the entire domain of the pore and some of its limitations as well as useful information such as the significance of the entrance effect
*WINNER* Career decision-making in college students: A path analysis of early childhood attachment, gender, age, and socioeconomic status
No full textCareer decision-making and identifying the associated variables that influence career development has been an area of considerable interest throughout vocational and occupational literature. The purpose of this study was to explore the effect of gender, age, socioeconomic status, and early childhood parental attachment on career decision-making. Participants included 309 college students who completed a demographic questionnaire, the Adult Scale of Parental Attachment-Short Form (ASPA-SF), and My Vocational Situation (MVS). Responses were examined through structural equation modeling using a path analysis in AMOS. Results indicated an overall acceptable model fit and the specific strength the corresponding variables had on career decision-making. Implications and areas for future research are proposed
Classifying Covid-19 X-Rays and exploring the relationships of associated data
No full textImage classification techniques using machine learning are proving to be very efficient in classifying medical images. In this paper we will look at a public Covid-19 Image dataset accompanied by clinical data to see what we can learn from our data. The data being used is a publicly available data set of labeled chest X-Ray images along with clinical data which includes parameters such as age, gender, diagnosis, and clinical notes. Using this data, we will answer some of the following questions. What is the performance difference of popular ML models including CNNs, SVMs and KNNs? What relationships exist in the parameters found in the clinical data? Can we successfully classify other features in our dataset? Can we use a multimodal approach to increase our model performance? We will be using AUC-ROC curve to validate our findings
Predicting Functionality of Tanzanian Waterpoints
No full textIn modern Tanzania, many residents rely on local water pumps as their primary source of fresh water. As such, it is important that these pumps remain functional, and that any potential issues are identified and dealt with swiftly for the well-being of the Tanzanian people. Using data collected by the Tanzania Ministry of Water and organized with the Taarifa data management interface, our goal was to accurately predict the function status of waterpoints in Tanzania. We did this using machine learning algorithms to analyze the forty given features to create a model that can assess whether a pump is functional, nonfunctional, or functional but in need of repair. We completed this research as part of a competition hosted by DrivenData, and so we assessed our results using DrivenData's prediction rate accuracy metric
*WINNER* Data Mining for Cardiovascular Disease Prediction
No full textCardiovascular diseases (CVDs) are disorders of the heart and blood vessels and are a major cause of disability and early death worldwide. For example, in the USA, one person dies every 36 seconds due to CVDs. In addition, it affects national income due to the cost of health care services, medicines, and lost productivity due to death. It's important to early notification for the individual at higher risk of developing CVD to prevent early deaths. Most often it's challenging for medical practitioners to predict cardiovascular disease as it requires experience and knowledge. The advances in the field of computational intelligence, together with the massive amount of data produced every day in clinical settings, have made it possible to create recognition systems capable of predicting whether an individual has CVD. Support Vector Machine (SVM), and Convolutional Neural Network (CNN) will be used to train on the Kaggle dataset of CVD cases, which includes 70000 registers of patients and 12 attributes divided into three types (Objective, Examination, and Subjective) considered relevant for identifying the disease. A feature weight is used to select which features are more useful in the training process in order to achieve a better accuracy
Of Rosin materials towards pharmaceutical and environmental purposes
No full textIndustrial environments are found across the world, and have directly contributed to the increase in factories as a result. However, there are also serious issues that have arisen from these industries, with major concerns pertaining to their toxic vapors, wastes, byproducts, and water contamination by metals (mercury and lead).The best option to remove these metals is to use an environmentally conscious ligand; one option is to use a bio-renewable, biodegradable, and environmentally friendly material to bind and extract metals from various materials. Other concerns include drawbacks from the pharmaceutical industry such as poor water solubility and dissolution rates of many drugs. One way to address this issue is by using the prodrug strategy. An FDA approved material Rosin, a binder for pharmaceutical tablets, can be used to address both of the aforementioned issues; the main component is a carboxylic acid (abietic acid) and can form esters with hydroxy-comprised compounds (imidazole-thiones or hydroxyl groups). The produced esters can form metallic complexes with heavy metals (imidazole-thione materials) or deliver a drug into an aqueous environment (through a prodrug strategy). In addition, the hydrolysis of the rosin esters will allow for its recovery. Here, we present our efforts towards developing such rosin esters as bio-renewable, biodegradable ligands for removal of heavy metals from the environment, and as potential drug delivery systems
Optimization of Annealing Temperature in Polymerase Chain Reaction on Constructing a Arrestin Variant (Arr3T137W)
Get PDFPolymerase chain reaction (PCR) is one of the most prevalent and effective methods implemented in cloning, sequencing, and DNA profiling. Among the three essential steps in PCR: denaturation (95 °C), annealing and elongation (72 °C), the annealing temperature could impact the amplification of the targeted DNA fragments. This experiment evaluated the effects of annealing temperature on PCR effectiveness and the optimal temperature for maximum yield and precision. To construct a single tryptophan arrestin3 variant, we intend to replace the Threonine with tryptophan by PCR. The effectiveness of this procedure was examined using agarose gel electrophoresis. This enabled comparison to previously effective PCR analysis, for sample identification and product conformation. The control sample at 46°C yielded an accurate and viable PCR product. A deviation of 10°C above or below the control temperature was conducted and analyzed via the same method. The sample at 36°C yielded results similar to the control. However, the sample conducted at 56°C yielded no product due to the annealing efficacy has been dramatically decreased at elevated temperatures. For the tested PCR reaction, annealing temperatures in the range of 36-46°C are effective, whereas temperatures are not effective
Computational Design and Docking of Hamigeromycin B Natural Product Derivatives in 26 Human Kinases
No full textHamigeromycin B analogs are synthetic natural product derivatives with potential for mediating signal transduction in human kinases. To study potential activity, 11 Hamigeromycin analogs were constructed using MOE 2020 and optimized using AMBER14:EHT. The analogs were docked into 26 human kinase structures obtained from the Protein Data Bank using the Docking module of MOE 2020. The docking sites in each kinase were targeted using the Protein Frustratometer and Evolutionary Trace to characterize the energetics and evolutionary importance of amino acids for contributions to binding. The lowest binding free energy scores were used to determine the best binding and orientation of each analog. The data suggests that five kinases are potential targets. New compounds for study were computationally designed by modification of functional groups in the original analogs. All compounds were then subjected to further refinement using AM1 semiempirical quantum mechanics in Gaussian '09. The five kinases were all screened with a set of known HSP90 inhibitors, radicicol A and its derivatives. Functional group modifications were made to the radicicol compounds, and they were docked into the five kinases