Physical Sciences and Mathematics Commons^™

Grass And Forage Improvement: Temperate Forages, Chris J. Pollock, M. T. Abberton, M. O. Humphreys

IGC Proceedings (1993-2023)

Key points

1. Plant breeding has contributed significantly to the development of effective grassland production systems.

2. New technologies offer enhanced precision in breeding and access to wider genetic variation.

3. The requirement for more sustainable production systems will require genetic improvements in complex traits where the use of new technology will be vital.

Improving The Quality Of Products From Grassland, Nigel D. Scollan, R. J. Dewhurst, A. P. Moloney, J. J. Murphy

IGC Proceedings (1993-2023)

Key points

1. Consumers are increasingly aware of the links between diet and health, and place increasing emphasis on nutritional quality as a component of product quality.

2. Meat and milk products are rich sources of nutrients such as omega-3 (n-3) fatty acids and conjugated linoleic acid, which offer health benefits to consumers.

3. Green plants are the primary source of n-3 fatty acids in the food chain.

4. Grassland production systems have the potential to enhance the content of beneficial fatty acids, improve stability (from higher antioxidant content) and alter sensory attributes of meat and milk.

5. Grassland offers …

Agricultural Carbon Markets: How Could They Work?, Andrew Havens

Department of Environmental Studies: Undergraduate Student Theses

The resurgence of voluntary markets in which consumers can purchase carbon credits generated by agricultural carbon sequestration has brought up many questions for farmers looking to potentially enter the market. Past carbon markets, such as the Chicago Climate Exchange, ended when a recession hit, causing demand for credits to swiftly decline. How can modern voluntary markets face these challenges along with new ones and be successful? This research paper, completed as an undergraduate thesis project at the University of Nebraska-Lincoln, examines the economic and scientific factors behind soil carbon sequestration credits. An extended literature review combined with estimation of a …

Symbolic Computation Of Lump Solutions To A Combined (2+1)-Dimensional Nonlinear Evolution Equation, Jingwei He

USF Tampa Graduate Theses and Dissertations

This thesis aims to consider a (2+1)-dimensional nonlinear evolution equation and its lump solutions. Byusing symbolic computation, two classes of lump solutions are presented. And for two specific chosen examples, we will show three-dimensional plots and density plots to exhibit dynamical features of the lump solution, which are made by Maple plot tools.

Agricultural Carbon Markets: How Could They Work?, Andrew Havens

Honors Theses

The resurgence of voluntary markets in which consumers can purchase carbon credits generated by agricultural carbon sequestration has brought up many questions for farmers looking to potentially enter the market. Past carbon markets, such as the Chicago Climate Exchange, ended when a recession hit, causing demand for credits to swiftly decline. How can modern voluntary markets face these challenges along with new ones and be successful? This research paper, completed as an undergraduate thesis project at the University of Nebraska-Lincoln, examines the economic and scientific factors behind soil carbon sequestration credits. An extended literature review combined with estimation of a …

Rising Demand For Meat And Milk In Developing Countries: Implications For Grasslands-Based Livestock Production, C. L. Delgado

IGC Proceedings (1993-2023)

Key points

1. Meat and milk consumption in developing countries has grown three times as fast as in developed countries over the past 30 years.

2. By 2020, developing countries will consume 72 million metric tons (mmt) more meat and 152 mmt more milk compared to 2002/3, dwarfing developed-country increases of 9 mmt for meat and 18 mmt for milk.

3. Ruminant livestock will account for 27% of the increase in global meat consumption between 2003 and 2020, up from 23% over the previous two decades.

4. The inflation-adjusted prices of livestock and feed grains are expected to fall only …

Grassland In Ireland And The Uk, Myles Rath, S. Peel

IGC Proceedings (1993-2023)

Key points

1. Grassland is the dominant land use option in Ireland and the UK, and is characterised by a long growing season.

2. Dynamic, interactive systems of grassland management have been developed which combine high grass dry matter intakes with good sward quality. In the better grassland areas milk yields in excess of 7000 kg/cow are attainable with low levels of concentrate supplementation.

3. In the times to come, measures to protect the environment will constrain stocking rates, and fertiliser and manure use on intensive grassland enterprises.

4. A high proportion of beef and sheep farms participate in voluntary, …

Bcse: Blockchain-Based Trusted Service Evaluation Model Over Big Data, Fengyin Li, Xinying Yu, Rui Ge, Yanli Wang, Yang Cui, Huiyu Zhou

Big Data Mining and Analytics

The blockchain, with its key characteristics of decentralization, persistence, anonymity, and auditability, has become a solution to overcome the overdependence and lack of trust for a traditional public key infrastructure on third-party institutions. Because of these characteristics, the blockchain is suitable for solving certain open problems in the service-oriented social network, where the unreliability of submitted reviews of service vendors can cause serious security problems. To solve the unreliability problems of submitted reviews, this paper first proposes a blockchain-based identity authentication scheme and a new trusted service evaluation model by introducing the scheme into a service evaluation model. The new …

Big Data With Cloud Computing: Discussions And Challenges, Amanpreet Kaur Sandhu

Big Data Mining and Analytics

With the recent advancements in computer technologies, the amount of data available is increasing day by day. However, excessive amounts of data create great challenges for users. Meanwhile, cloud computing services provide a powerful environment to store large volumes of data. They eliminate various requirements, such as dedicated space and maintenance of expensive computer hardware and software. Handling big data is a time-consuming task that requires large computational clusters to ensure successful data storage and processing. In this work, the definition, classification, and characteristics of big data are discussed, along with various cloud services, such as Microsoft Azure, Google Cloud, …

Exploiting More Associations Between Slots For Multi-Domain Dialog State Tracking, Hui Bai, Yan Yang, Jie Wang

Big Data Mining and Analytics

Dialog State Tracking (DST) aims to extract the current state from the conversation and plays an important role in dialog systems. Existing methods usually predict the value of each slot independently and do not consider the correlations among slots, which will exacerbate the data sparsity problem because of the increased number of candidate values. In this paper, we propose a multi-domain DST model that integrates slot-relevant information. In particular, certain connections may exist among slots in different domains, and their corresponding values can be obtained through explicit or implicit reasoning. Therefore, we use the graph adjacency matrix to determine the …

Sampling With Prior Knowledge For High-Dimensional Gravitational Wave Data Analysis, He Wang, Zhoujian Cao, Yue Zhou, Zong-Kuan Guo, Zhixiang Ren

Big Data Mining and Analytics

Extracting knowledge from high-dimensional data has been notoriously difficult, primarily due to the so-called "curse of dimensionality" and the complex joint distributions of these dimensions. This is a particularly profound issue for high-dimensional gravitational wave data analysis where one requires to conduct Bayesian inference and estimate joint posterior distributions. In this study, we incorporate prior physical knowledge by sampling from desired interim distributions to develop the training dataset. Accordingly, the more relevant regions of the high-dimensional feature space are covered by additional data points, such that the model can learn the subtle but important details. We adapt the normalizing flow …

Toward Intelligent Financial Advisors For Identifying Potential Clients: A Multitask Perspective, Qixiang Shao, Runlong Yu, Hongke Zhao, Chunli Liu, Mengyi Zhang, Hongmei Song, Qi Liu

Big Data Mining and Analytics

Intelligent Financial Advisors (IFAs) in online financial applications (apps) have brought new life to personal investment by providing appropriate and high-quality portfolios for users. In real-world scenarios, identifying potential clients is a crucial issue for IFAs, i.e., identifying users who are willing to purchase the portfolios. Thus, extracting useful information from various characteristics of users and further predicting their purchase inclination are urgent. However, two critical problems encountered in real practice make this prediction task challenging, i.e., sample selection bias and data sparsity. In this study, we formalize a potential conversion relationship, i.e., user→activated user→client and decompose this relationship into …

A Comparison Of Computational Approaches For Intron Retention Detection, Jiantao Zheng, Cuixiang Lin, Zhenpeng Wu, Hong-Dong Li

Big Data Mining and Analytics

Intron Retention (IR) is an alternative splicing mode through which introns are retained in mature RNAs rather than being spliced in most cases. IR has been gaining increasing attention in recent years because of its recognized association with gene expression regulation and complex diseases. Continuous efforts have been dedicated to the development of IR detection methods. These methods differ in their metrics to quantify retention propensity, performance to detect IR events, functional enrichment of detected IRs, and computational speed. A systematic experimental comparison would be valuable to the selection and use of existing methods. In this work, we conduct an …

Reducing Loading On The Contralateral Limb Using Human-In-The-Loop Optimization, Siena Senatore

UNO Student Research and Creative Activity Fair

In most everyday activities, we head towards a specific goal by updating our choices for a more direct path. However, there are specific clinical tasks where taking the direct path is more challenging. Clinical investigations of optimizing a prosthesis involve the assessment of multiple parameter settings through trial and error rather than goal-directed optimization. We investigate if a human-in-the-loop optimization algorithm can guide manual alterations to a prosthesis-simulating device to reduce the ground reaction force on the contralateral limb. In most participants, the optimal condition reduced the loading rate on the contralateral limb compared to the initial condition tested. These …

A Critical Comparison Of Brave Browser And Google Chrome Forensic Artefacts, Stuart Berham, Sarah Morris

Journal of Digital Forensics, Security and Law

Digital forensic practitioners are tasked with the identification, recovery and analysis of Internet browser artefacts which may have been used in the pursuit of committing a civil or criminal offence. This research paper critically compares the most downloaded browser, Google Chrome, against an increasingly popular Chromium browser known as Brave, said to offer privacy-by-default. With increasing forensic caseloads, data complexity, and requirements for method validation to satisfy ISO 17025 accreditation, recognising the similarities and differences between the browsers, developed on the same underlying technology is essential. The paper describes a series of conducted experiments and subsequent analysis to identify artefacts …

Team Coordination Dynamics Of Winning Nba Teams, Alli Grunkemeyer, Joel H. Sommerfeld

UNO Student Research and Creative Activity Fair

Predicting sports games outcomes is an endless pursuit shared by stakeholders ranging from fans to coaches to data scientists. We have begun investigating the value of positional data recorded during basketball gameplay with the goal of predicting outcomes from team dynamics as they emerge. We approached this problem by analyzing the “shape” of team movements on the court and investigated whether team dynamics in NBA games mimicked long-range correlated patterns observed in other team contexts. We analyzed 622 NBA games from an archival data set, including all area time series obtained for each of the four quarters. We fit a …

Design And Development Of Software With A Graphical User Interface To Display And Convert Multiple Microscopic Histology Images, Sayed Ahmadreza Razian, Majid Jadidi, Alexey Kamenskiy

UNO Student Research and Creative Activity Fair

Histological images are widely used to assess the microscopic anatomy of biological tissues. Recent advancements in image analysis allow the identification of structural features on histological sections that can help advance medical device development, brain and cancer research, drug discovery, vascular mechanobiology, and many other fields. Histological slide scanners create images in SVS and TIFF formats that were designed to archive image blocks and high-resolution textual information. Because these formats were primarily intended for storage, they are often not compatible with conventional image analysis software and require conversion before they can be used in research. We have developed a user-friendly …

The Fierce Green Fire: Vol. 12 Issue 12, Wofford College. Department Of Environmental Studies

The Fierce Green Fire

No abstract provided.

Three Wave Mixing In Epsilon-Near-Zero Plasmonic Waveguides For Signal Regeneration, Nicholas Mirchandani, Mark C. Harrison

Engineering Faculty Articles and Research

Vast improvements in communications technology are possible if the conversion of digital information from optical to electric and back can be removed. Plasmonic devices offer one solution due to optical computing’s potential for increased bandwidth, which would enable increased throughput and enhanced security. Plasmonic devices have small footprints and interface with electronics easily, but these potential improvements are offset by the large device footprints of conventional signal regeneration schemes, since surface plasmon polaritons (SPPs) are incredibly lossy. As such, there is a need for novel regeneration schemes. The continuous, uniform, and unambiguous digital information encoding method is phase-shift-keying (PSK), so …

Translation Of: Dupin’Sche Hyperflächen, Doctoral Dissertation, Universität Freiburg (1981) By Ulrich Pinkall, Thomas E. Cecil

Mathematics and Computer Science Department Faculty Scholarship

This is an unofficial translation of the original dissertation which was written in German. A few minor typographical errors have been corrected by the translator. All references should be made to the original dissertation. The classification of Dupin hypersurfaces in E⁴ contained in this dissertation is also contained in the journal article by Ulrich Pinkall, Dupin’sche Hyperflächen in E⁴, Manuscr. Math. 51 (1985), 89–119.

Pseudo-Stereo For Monocular 3d Object Detection In Autonomous Driving, Yi-Nan Chen, Hang Dai, Yong Ding

Computer Vision Faculty Publications

Pseudo-LiDAR 3D detectors have made remarkable progress in monocular 3D detection by enhancing the capability of perceiving depth with depth estimation networks, and using LiDAR-based 3D detection architectures. The advanced stereo 3D detectors can also accurately localize 3D objects. The gap in image-to-image generation for stereo views is much smaller than that in image-to-LiDAR generation. Motivated by this, we propose a Pseudo-Stereo 3D detection framework with three novel virtual view generation methods, including image-level generation, feature-level generation, and feature-clone, for detecting 3D objects from a single image. Our analysis of depth-aware learning shows that the depth loss is effective in …

Moving Toward Personalized Law, Cary Coglianese

All Faculty Scholarship

Rules operate as a tool of governance by making generalizations, thereby cutting down on government officials’ need to make individual determinations. But because they are generalizations, rules can result in inefficient or perverse outcomes due to their over- and under-inclusiveness. With the aid of advances in machine-learning algorithms, however, it is becoming increasingly possible to imagine governments shifting away from a predominant reliance on general rules and instead moving toward increased reliance on precise individual determinations—or on “personalized law,” to use the term Omri Ben-Shahar and Ariel Porat use in the title of their 2021 book. Among the various technological, …

An Industry Life Cycle Assessment (Lca) For Sheep Production In Western Australia, Stephen Wiedemann, Darcia Mcrae, Emma Longworth

Animal production research reports

The Western Australian Department of Primary Industries and Regional Development (DPIRD) has identified the need to understand greenhouse gas (GHG) emissions from the livestock sector in detail, with a view to developing emission reduction plans for the state. To achieve this, DPIRD commissioned a life cycle assessment (LCA) for the sheep industry in Western Australia (WA) for the financial years (FY) 2005 (July 1, 2004 to June 30, 2005) and 2020 (July 1, 2019 to June 30, 2020). The analysis of one historic period provided a baseline reference point for the more recent results, and the intent was to develop …

Ingredient Classification Using Food Ontology, Ricky Flores

UNO Student Research and Creative Activity Fair

A food label provides some of the most crucial information for a food product. The food label is a key resource for many health-conscious consumers for understanding ingredients. It is also vital for individuals to avoid food allergens or help patients follow dietary recommendations. While the food labels in the United States are regulated by the Food and Drug Administration (FDA) many labels contain additional information or statements that are not regulated. Moreover, the food label may be complex or contain terminology that the layperson may not understand. Evidence has indicated that consumers often find nutrition labels confusing, especially when …

Multiple Periodic Vibrations Of Auxetic Honeycomb Sandwich Plate With 1:2 Internal Resonance, Shaotao Zhu, Jing Li, Zhijun Qiao, Ji Zhou

School of Mathematical and Statistical Sciences Faculty Publications and Presentations

In this paper, we focus on the multiple periodic vibration behaviors of an auxetic honeycomb sandwich plate subjected to in-plane and transverse excitations. Nonlinear equation of motion for the plate is derived based on the third-order shear deformation theory and von Kármán type nonlinear geometric assumptions. The Melnikov method is extended to detect the bifurcation and multiple periodic vibrations of the plate under 1:2 internal resonance. The effects of transverse excitation on nonlinear vibration behaviors are discussed in detail. Evolution laws and waveforms of multiple periodic vibrations are obtained to analyze the energy transfer process between the first two order …

Solid State Nmr Spectroscopic Characterization Of Metal Organic Frameworks, Vinicius Martins

Electronic Thesis and Dissertation Repository

Metal-organic frameworks are porous organic-inorganic materials that have attracted enormous attention due to their promising capabilities for several technologies, including carbon dioxide capture and storage, gas separation, and heterogeneous catalysis. The performance of MOFs for these applications is directly linked to their properties and, by extension, structures. Therefore, it is essential to understand the structure – property relationship. Solid-state NMR (SSNMR) spectroscopy is a technique that provides complementary information to X-ray diffraction-based techniques. SSNMR can provide short-range information around the NMR-active nucleus of interest. Furthermore, SSNMR can provide additional information regarding host-guest interactions and dynamics of adsorbed molecules, which play …

The Role Of Transient Vibration Of The Skull On Concussion, Rodrigo Dalvit Carvalho Da Silva

Electronic Thesis and Dissertation Repository

Concussion is a traumatic brain injury usually caused by a direct or indirect blow to the head that affects brain function. The maximum mechanical impedance of the brain tissue occurs at 450±50 Hz and may be affected by the skull resonant frequencies. After an impact to the head, vibration resonance of the skull damages the underlying cortex. The skull deforms and vibrates, like a bell for 3 to 5 milliseconds, bruising the cortex. Furthermore, the deceleration forces the frontal and temporal cortex against the skull, eliminating a layer of cerebrospinal fluid. When the skull vibrates, the force spreads directly to …

Analysis Of Groundwater Recharge In Mongolian Drylands Using Composite Vadose Zone Modeling, Khulan Batsukh, Vitaly A. Zlotnik, Paolo Nasta

Department of Earth and Atmospheric Sciences: Faculty Publications

Knowledge of groundwater recharge (GR) is important for the effective management of water resources under semi-arid continental climates. Unfortunately, studies and data in Mongolia are limited due to the constraints in funding and lack of research infrastructures. Currently, the wide accessibility of freely available global-scale digital datasets of physical and chemical soil properties, weather data, vegetation characteristics, and depths to the water table offers new tools and basic information that can support low-cost physically based and process-oriented models. Estimates of GR over 41 study sites in Mongolia were obtained using HYDRUS-1D in a 2-m-thick soil profile with root …

Ad-Corre: Adaptive Correlation-Based Loss For Facial Expression Recognition In The Wild, Ali Pourramezan Fard, Mohammad H. Mahoor

Electrical and Computer Engineering: Faculty Scholarship

Automated Facial Expression Recognition (FER) in the wild using deep neural networks is still challenging due to intra-class variations and inter-class similarities in facial images. Deep Metric Learning (DML) is among the widely used methods to deal with these issues by improving the discriminative power of the learned embedded features. This paper proposes an Adaptive Correlation (Ad-Corre) Loss to guide the network towards generating embedded feature vectors with high correlation for within-class samples and less correlation for between-class samples. Ad-Corre consists of 3 components called Feature Discriminator, Mean Discriminator, and Embedding Discriminator. We design the Feature Discriminator component to guide …

Digital Discrimination In The Sharing Economy: Evidence, Policy, And Feature Analysis, Miroslav Tushev

LSU Doctoral Dissertations

Applications (apps) of the Digital Sharing Economy (DSE), such as Uber, Airbnb, and TaskRabbit, have become a main facilitator of economic growth and shared prosperity in modern-day societies. However, recent research has revealed that the participation of minority groups in DSE activities is often hindered by different forms of bias and discrimination. Evidence of such behavior has been documented across almost all domains of DSE, including ridesharing, lodging, and freelancing. However, little is known about the under- lying design decisions of DSE systems which allow certain demographics of the market to gain unfair advantage over others. To bridge this knowledge …