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Spray Characterization And Fuel Property Analysis Of Tier 3 Gasoline In A Gdi System Using Machine Learning, Kyungwon Lee Aug 2025

Spray Characterization And Fuel Property Analysis Of Tier 3 Gasoline In A Gdi System Using Machine Learning, Kyungwon Lee

Theses and Dissertations

This study investigates the spray behavior of Tier 3 gasoline in gasoline direct injection engines using experimental methods. Tier 3 gasoline, formulated with lower sulfur content, enhances aftertreatment system efficiency and supports cleaner combustion. A comparative fuel property analysis between Tier 3 gasoline and PACE-20, surrogate fuel, was conducted to understand compositional effects on spray. A constant volume spray chamber and optical diagnostics, including diffuse back-illumination extinction, Schlieren, microscopic, and 3D CT reconstruction imaging, were used to examine spray morphology under varying injection conditions. Key spray parameters such as liquid volume fraction, projected liquid volume, droplet size, and cone angle …


“It Just Builds Character”: Building The Bullying Myths Scale, Jessica Weiss Utley Aug 2025

“It Just Builds Character”: Building The Bullying Myths Scale, Jessica Weiss Utley

Theses and Dissertations

Approximately 20% of American children and adolescents report being victims of bullying each year (Irwin et al., 2022). Bullying victimization is linked to serious behavioral and psychological outcomes, like depression, anxiety, self-harm, and suicide (e.g., Chou et al., 2020; John et al., 2018; Mulder et al., 2017; Schoeler et al., 2018). Despite these sobering data, misconceptions continue to portray bullying as a normal part of growing up, that it is trivial in nature, and that some kids deserve to be bullied (Dawes et al., 2022; Kulig et al., 2008). This study tested the validity and efficacy of the Bullying Myths …


Advancing Rangeland Vegetation Mapping Through Integrated Uav And Satellite Imagery: A Comparative Machine Learning Framework For Fractional Cover Classification, Nishat Shermin Aug 2025

Advancing Rangeland Vegetation Mapping Through Integrated Uav And Satellite Imagery: A Comparative Machine Learning Framework For Fractional Cover Classification, Nishat Shermin

Theses and Dissertations

This study presents a multi-scale remote sensing framework to classify fractional vegetation cover (FVC) across rangelands by integrating UAV multispectral imagery, LiDAR structural data, and multisource satellite inputs. Four machine learning models, ranging from UAV-only to fused UAV-LiDAR-Sentinel models, were developed and evaluated using Random Forest (RF) and Extreme Gradient Boosting (XGBoost) algorithms. The research was conducted at Martin Ranch, Texas, using Uncrewed Ariel Vehicle (UAV)-collected multispectral imagery, LiDAR-derived canopy height, and Sentinel-1/2 indices. Model 2 (UAV + LiDAR) emerged as the optimal model for balancing accuracy, processing time, and compatibility with ecological simulation tools. This model captures both spectral …


Evaluation Of Soil Steaming, Cover Crops, And Allelopathy: An Integrated And Sustainable Weed Management Strategy In Sweetpotatoes, Alaina Marie Richardson Aug 2025

Evaluation Of Soil Steaming, Cover Crops, And Allelopathy: An Integrated And Sustainable Weed Management Strategy In Sweetpotatoes, Alaina Marie Richardson

Theses and Dissertations

Yellow nutsedge (Cyperus esculentus L.) is a persistent weed in sweetpotato and vegetable cropping systems caused by its aggressive growth habit and limited control options. The present study assessed two alternative, chemical-free methods: steaming the soil and the use of allelopathic cover crops. Greenhouse and field experiments showed that steaming suppressed the germination of yellow nutsedge effectively and that treatments for 45 min provided the highest control of all the soil depths tested (100%). A leachate experiment examined the allelopathy of five cover crops against yellow nutsedge and showed that buckwheat and cereal rye had the largest reductions in shoot …


Neural Architecture Search-Driven Unsupervised Domain Adaptation For Enhanced Wood Chip Quality Evaluation In Forest Industries, Abdur Rahman Aug 2025

Neural Architecture Search-Driven Unsupervised Domain Adaptation For Enhanced Wood Chip Quality Evaluation In Forest Industries, Abdur Rahman

Theses and Dissertations

Reliable and efficient measurement of wood chip moisture content is crucial for forest-reliant industries, including biofuel production, pulp and paper manufacturing, and bio-refineries, as it directly influences product quality and energy output. Traditional methods like the oven-drying technique, despite their widespread use, are time-consuming and impractical for real-time applications, while modern alternatives such as NIR spectroscopy, electrical capacitance, and microwave analysis are often costly, less portable, and require specialized expertise. This dissertation addresses these limitations by leveraging deep learning and machine vision to develop a scalable, accurate, and portable method for moisture content measurement using RGB images of wood chips. …


Reactive Molecular Dynamics And Method Development For Applications In Renewable Energy And Sorption Equilibria, Woodrow Wilson Aug 2025

Reactive Molecular Dynamics And Method Development For Applications In Renewable Energy And Sorption Equilibria, Woodrow Wilson

Theses and Dissertations

It is crucial to harness energy from sustainable sources to combat the dwindling nonrenewable feedstocks used to produce everyday commodities and fuels. Liquid-phase heterogeneous catalysis has demonstrated remarkable product selectivity and yields for reactions relevant to biomass valorization under mild operating conditions. However, active site characterization is challenging due to the complex solvated environment and interface. Ground-state first-principles (FP) molecular simulations have provided insights into reactive systems in catalysis. These calculations, however, scale poorly with the number of electrons. Observing atomic motion with molecular dynamics (MD) or sampling static properties with Monte Carlo (MC) simulations at statistically relevant lengths- and …


Interatomic Potential Of Multiphase Materials Using Modified Embedded Atom Method (Meam) And Artificial Neural Network (Rann), Henan Zhou Aug 2025

Interatomic Potential Of Multiphase Materials Using Modified Embedded Atom Method (Meam) And Artificial Neural Network (Rann), Henan Zhou

Theses and Dissertations

There is a significant need for computer simulations to explore multiphase materials because of their significance in both industry and research. These simulations are both more efficient and less expensive than many experimental approaches, making them an ideal choice for this purpose. It is possible to use molecular dynamics simulations that make use of the MEAM and RANN interatomic potentials in order to comprehend and characterize the properties, performance, and behavior of materials at the atomic scale of different material phases. In the realms of elements, alloys, and impurities, MEAM can be utilized in a wide variety of applications. Through …


Soil Ethics In Practice: Harvesting Conservation Choices Among Puerto Rican Coffee Farmers, Patricia Marie Cordero-Irizarry Aug 2025

Soil Ethics In Practice: Harvesting Conservation Choices Among Puerto Rican Coffee Farmers, Patricia Marie Cordero-Irizarry

Theses and Dissertations

Coffee farming in Puerto Rico has declined over recent decades, partly due to deteriorating soil quality. However, the decision-making process behind farmers’ adoption of soil conservation practices remains unclear, particularly the overlooked role of soil ethics, which emphasizes the moral principles guiding human relationships with the soil. This mixed-methods study examined coffee farmers’ adoption of soil conservation practices by integrating the Values-Beliefs-Norms (VBN) theory and a newly developed Soil Ethics Survey (SES) instrument for the quantitative component, while using Decision-Making Theory and Social Cognitive Theory to qualitatively explore how farmers’ experiences and reflections shape their soil ethics. Quantitative findings revealed …


Evaluating The Impacts Of Cover Crops At Different Nitrogen Rates On Soil Microbial Dynamics Within A Sweetpotato Production System, Lahari Nekkalapudi Aug 2025

Evaluating The Impacts Of Cover Crops At Different Nitrogen Rates On Soil Microbial Dynamics Within A Sweetpotato Production System, Lahari Nekkalapudi

Theses and Dissertations

A field study was conducted from 2023 to 2024 at Pontotoc, Mississippi, to evaluate the effects of cover crops and nitrogen (N) fertilizer on soil microbial communities in sweet potato production. The study followed a randomized split-block design with three cover crops (Clover, Wheat, and Fallow) and three N rates (0, 50, and 100 lb N acre⁻¹), each replicated four times. Soil samples were collected at cover crop termination, sweet potato planting, and harvest. Bacterial and fungal communities were analyzed using Illumina HiSeq sequencing. Soil properties such as total carbon, total nitrogen, pH, POXC, and microbial activity (AWCD) were also …


Optical Trapping For The Study Of The Chemical And Physical Dynamics Of Single Particles, Yukai Ai Aug 2025

Optical Trapping For The Study Of The Chemical And Physical Dynamics Of Single Particles, Yukai Ai

Theses and Dissertations

This dissertation explores the combined technique of optical trapping and Raman spectroscopy (OT-RS) to study the physical and chemical properties, as well as the dynamic surface changes, of single aerosol particles in air. The study covers a wide range of aerosol types, including bioaerosols (such as pollen, bacteria, and fungi), dust particles (such as black carbon, terrestrial, and extraterrestrial materials), and liquid droplets (such as sea-spray aerosols). The optical trapping system used in this work is based on the universal optical trap (UOT), which is capable of trapping and manipulating a wide variety of particle types. These include both transparent …


A Note On Psoloessa Texana And Achurum Sumichrasti (Orthoptera: Acrididae: Acridinae) From Louisiana, Jovonn G. Hill Aug 2025

A Note On Psoloessa Texana And Achurum Sumichrasti (Orthoptera: Acrididae: Acridinae) From Louisiana, Jovonn G. Hill

Midsouth Entomologist

During a 2024 survey in Kisatchie National Forest, Louisiana, Psoloessa texana and Achurum sumichrasti were collected, representing new state records. No prior records of P. texana exist for Louisiana, and while A. sumichrasti has been observed and reported online, no specimens were previously documented. These findings extend the known range of P. texana by ~320 km and suggest a broader distribution for A. sumichrasti. Their presence in xeric savannas may reflect Pleistocene-era disjunctions. With these additions, Louisiana’s documented grasshopper fauna increases to 41 species.


Formosan Subterranean Termites Coptotermes Formosanus Shiraki (Blattodea: Heterotermitidae): An Underreported Threat To Commercial Shrimp Boats In The Midsouth, Usa, J. S. Portugal Iii Aug 2025

Formosan Subterranean Termites Coptotermes Formosanus Shiraki (Blattodea: Heterotermitidae): An Underreported Threat To Commercial Shrimp Boats In The Midsouth, Usa, J. S. Portugal Iii

Midsouth Entomologist

No abstract provided.


Bioassay To Evaluate Resistance Levels In Tarnished Plant Bug (Hemiptera: Miridae) Populations In Alabama To Common Cotton Insecticides, T. J. Douglas, K. Kesheimer, A. Jacobson, S. Brown, F. R. Musser, L. S. Catchot, S. H. Graham Aug 2025

Bioassay To Evaluate Resistance Levels In Tarnished Plant Bug (Hemiptera: Miridae) Populations In Alabama To Common Cotton Insecticides, T. J. Douglas, K. Kesheimer, A. Jacobson, S. Brown, F. R. Musser, L. S. Catchot, S. H. Graham

Midsouth Entomologist

The tarnished plant bug, Lygus lineolaris (Palisot de Beauvois), has emerged as the major insect pest of cotton in the mid-southern United States following the eradication of the boll weevil and the introduction of genetically modified Bt cotton for caterpillar pests. The objective of this study is to evaluate tarnished plant bug resistance to the five most common insecticides used for control across six distinct growing regions. Glass-vial bioassays were used to evaluate resistance of field populations in a laboratory setting. Elevated levels of resistance of tarnished plant bug to bifenthrin and, to a lesser degree, imidacloprid have been reported …


Ground Truthing Of Inaturalist Submissions Confirms The Presence Of Asian Needle Ants, Brachyponera Chinensis (Emery) (Hymenoptera: Formicidae), In Louisiana, A New State Record, Aaron R. Ashbrook, Victoria Bayless, Stephen Baca, Gerardo Guevara-Milla, Chris E. Carlton Aug 2025

Ground Truthing Of Inaturalist Submissions Confirms The Presence Of Asian Needle Ants, Brachyponera Chinensis (Emery) (Hymenoptera: Formicidae), In Louisiana, A New State Record, Aaron R. Ashbrook, Victoria Bayless, Stephen Baca, Gerardo Guevara-Milla, Chris E. Carlton

Midsouth Entomologist

Based on submissions to iNaturalist from citizen scientists, the presence of the Asian needle ant (Brachyponera chinensis), was confirmed for Louisiana in East Baton Rouge Parish. Use of citizen scientist platforms for sources of invertebrate taxa distributions is a powerful tool but requires caution because the records are typically not validated by physical voucher specimens that have been deposited in publicly accessible museums, and identification of many species is not possible by images alone. To demonstrate the usefulness of citizen scientist programs like iNaturalist, possible collection sites for Asian needle ant specimens were located. Specimens were collected, identified, and vouchers …


What Mathematics Educators Can Learn From Collaborating With Special Educators, Liza Bondurant, Breana Jamison Aug 2025

What Mathematics Educators Can Learn From Collaborating With Special Educators, Liza Bondurant, Breana Jamison

Publications

No abstract provided.


2024 Soybean Insect Losses In The United States, Fred R. Musser, Sebe A. Brown, Tim Bryant, Whitney D. Crow, Jeffrey A. Davis, Christina Difonzo, Chase Floyd, Scott H. Graham, Jeremy K. Greene, Kelly A. Hamby, David Kerns, Janet Knodel, David Owens, Dominic D. Reisig, Phillip M. Roberts, Nicholas J. Seiter, Adam J. Sisson, Benjamin C. Thrash, Kelley J. Tilmon, Raul T. Villanueva Aug 2025

2024 Soybean Insect Losses In The United States, Fred R. Musser, Sebe A. Brown, Tim Bryant, Whitney D. Crow, Jeffrey A. Davis, Christina Difonzo, Chase Floyd, Scott H. Graham, Jeremy K. Greene, Kelly A. Hamby, David Kerns, Janet Knodel, David Owens, Dominic D. Reisig, Phillip M. Roberts, Nicholas J. Seiter, Adam J. Sisson, Benjamin C. Thrash, Kelley J. Tilmon, Raul T. Villanueva

Midsouth Entomologist

Estimated management costs and losses due to insects and other invertebrates in soybean during the 2024 growing season were collected and compiled from 19 states to provide a record of insect pressure and management practices for the year. These annual estimates provide a historical record of pest pressure and insect management and have been compiled in some states since 2004. Participating states represented 63% of soybean acreage grown in the United States, with near 100% participation in southern states. Overall, the stink bug complex was the costliest insect pest in soybean followed by corn earworm and soybean looper. Total insect …


Absence Of Superconductivity In The Lightly Doped Hubbard Model, Jodie Roberts, Rudolf Torsten Clay Jul 2025

Absence Of Superconductivity In The Lightly Doped Hubbard Model, Jodie Roberts, Rudolf Torsten Clay

Research Experiences for Undergraduates in Computational Methods with Applications in Materials Science

The mechanism of superconductivity (SC) in high critical temperature cuprate superconductors remains an unsolved problem. The simplest electronic model of cuprate superconductors is the one band Hubbard model. It models copper atom positions with lattice sites, omitting oxygen atoms for simplicity, and separates the Hamiltonian into hopping (t,t) and interaction (U) components. The simplest Hubbard model only considers nearest neighbor hopping, t. To account for overlap between oxygen orbitals also requires next nearest neighbor hopping, t'. Exact solutions of the model are computationally prohibitive to find for large systems. Quantum Monte Carlo (QMC) methods such as Constrained Path Monte Carlo …


Neural Network Prediction Of Titanium-Aluminum Mechanical Properties, Carter Reed, Kip Barrett Jul 2025

Neural Network Prediction Of Titanium-Aluminum Mechanical Properties, Carter Reed, Kip Barrett

Research Experiences for Undergraduates in Computational Methods with Applications in Materials Science

Technological progress is strongly coupled with our understanding of materials. In fields like aerospace, titanium-aluminum (Ti-Al) alloys are of particular interest for their strength-to-weight ratio and high-temperature performance. The ability to accurately predict these characteristics as a function of composition and processing conditions would reduce research costs by tuning the performance to the application's needs before producing the physical material. The mechanical properties, and performance by proxy, of a material are dependent on the microstructure of and the interatomic interactions within the material. Thus, we validate the rapid artificial neural network (RANN) potential of the titanium-aluminum binary system for the …


Efficient Image Denoising Models With Anderson Acceleration Using Finite Difference Methods, Amanda E. Diegel, Spence Hanegan, Hyeona Lim, Hoang Tran Jul 2025

Efficient Image Denoising Models With Anderson Acceleration Using Finite Difference Methods, Amanda E. Diegel, Spence Hanegan, Hyeona Lim, Hoang Tran

Research Experiences for Undergraduates in Computational Methods with Applications in Materials Science

Current image denoising algorithms based on variational methods can suffer from slow convergence or no convergence due to  high nonlinearity of the images. To speed up the convergence of denoising, we apply Anderson acceleration to the fixed-point image denoising problem. Anderson acceleration is an algorithmic method for reducing the number of fixed-point iterations necessary for convergence. It involves using weighted updates to each iteration based on the weighted residuals from past iterations, or history. By using finite difference methods, we can approximate the gradient and higher-order partial derivatives at points on the image. We then use these approximations to create …


Developing A Computational Pipeline For Microstructure-Based Modelling With Exaca And Evpfft, Lizzy Beall, Eric Collins, Jacob Moore Jul 2025

Developing A Computational Pipeline For Microstructure-Based Modelling With Exaca And Evpfft, Lizzy Beall, Eric Collins, Jacob Moore

Research Experiences for Undergraduates in Computational Methods with Applications in Materials Science

The microstructure of a metal determines its properties and by understanding the grains that make up that structure, we can predict the behavior of that material. However, it can be difficult and costly to view the microstructure of a metal, especially since the microstructure is highly dependent on the manufacturing history of the part. By computer generating the microstructure of a material, we can better understand its properties. Exascale Cellular Automata (ExaCA) can generate a microstructure for a metal sample given its thermal history and Elasto-Visco Plastic Fast Fourier Transforms (EVPFFT) can model the response of the crystals in a …


Virtual Screening Of Peptides That Can Prevent Insulin Aggregation, Thanh Tien Dao, Bidisha Sengupta, Steven Gwaltney Jul 2025

Virtual Screening Of Peptides That Can Prevent Insulin Aggregation, Thanh Tien Dao, Bidisha Sengupta, Steven Gwaltney

Research Experiences for Undergraduates in Computational Methods with Applications in Materials Science

Diabetes is a growing health concern, with almost 3% of the population of the United States using insulin injections to control blood sugar levels. Insulin is prone to aggregation during storage and injection. The toxic products of aggregation can cause an increase in the required dosage to achieve the desired therapeutic effect. The driving intermediate of aggregation is believed to be a partially folded insulin, derived from the insulin monomer. We hypothesize that stabilizing the insulin monomer with a peptide may prevent this unfolding process and subsequent aggregation. However, the space of all possible peptides is impossibly large to study …


Developing A Neural Network For Prediction Of Interatomic Energies In Iron-Manganese Alloys, Robert D. H. Race, Doyl Dickel, Hala Ben Messaoud Jul 2025

Developing A Neural Network For Prediction Of Interatomic Energies In Iron-Manganese Alloys, Robert D. H. Race, Doyl Dickel, Hala Ben Messaoud

Research Experiences for Undergraduates in Computational Methods with Applications in Materials Science

Machine-learned interatomic potentials (ML IAP) for alloy systems have been sought after due to their ability to reduce experimentation costs and time, accelerating alloy development and discovery. However, the explicit inclusion of magnetism in these potentials has been both a difficult and important problem to solve, due to the complexity of spin-lattice dynamics and its significance in the properties of magnetic alloys. We present here the development of an explicitly magnetic Fe-Mn ML IAP using a physics informed neural network (PINN) extension of the rapid artificial neural network (RANN) formalism. It is shown that the potential is capable of reproducing …


Computational Investigation Of Substituent Effects On Zirconium Pincer Complexes Via Density Functional Theory Methods, Anna Constable, Garrett M. Wells, Samuel D. Juarez Escamilla, Thedford K. Hollis, Charles Edwin Webster Jul 2025

Computational Investigation Of Substituent Effects On Zirconium Pincer Complexes Via Density Functional Theory Methods, Anna Constable, Garrett M. Wells, Samuel D. Juarez Escamilla, Thedford K. Hollis, Charles Edwin Webster

Research Experiences for Undergraduates in Computational Methods with Applications in Materials Science

Organic light-emitting diodes (OLEDs) have emerged as a promising technology for displays due to their high efficiency and superior color performance. The primary objective of this study was to investigate the tunability of zirconium carbene "pincer" complexes for potential use in OLED applications. Specifically, we aim to understand how changes in coordinated ligands and their substituents influence the electronic structure and spectral properties. A series of computational tests were conducted using density functional theory (DFT) to optimize the ground-state geometries and time-dependent density functional theory (TD-DFT) to optimize the excited-state geometries. TD-DFT calculations are also used to predict absorption and …


Investigating The Defect Behavior And Electronic Properties Of Formamidinium Lead Bromide Perovskite Through Machine Learned Interatomic Potentials, Rachel Lee, John Michael Lane, Woodrow Wilson, Neeraj Rai Jul 2025

Investigating The Defect Behavior And Electronic Properties Of Formamidinium Lead Bromide Perovskite Through Machine Learned Interatomic Potentials, Rachel Lee, John Michael Lane, Woodrow Wilson, Neeraj Rai

Research Experiences for Undergraduates in Computational Methods with Applications in Materials Science

Formamidinium lead bromide (FAPbBr3) perovskite crystals display promising optoelectronic properties, making them attractive materials for solar cells, light-emitting diodes, and photoelectrochemical devices. In this study, computational methods are applied to investigate the effects of point defects—vacancies, interstitials, Frenkel, and Schottky—on the electronic structure of FAPbBr3 bulk and nanoplatelet crystals. Traditional computational methods, such as density functional theory (DFT), are computationally expensive and thus limited to small systems and short time scales. To characterize and simulate larger systems over longer time periods at reduced computational costs, machine learned interatomic potentials (MLIPs) are developed with MACE, a message passing neural network. The …


Anomaly Detection In Material Images Using Scan Statistics, Kaitlyn Anderson, Asanka Duwage, Tung-Lung Wu Jul 2025

Anomaly Detection In Material Images Using Scan Statistics, Kaitlyn Anderson, Asanka Duwage, Tung-Lung Wu

Research Experiences for Undergraduates in Computational Methods with Applications in Materials Science

Nanoproducts are a growing sector due to their unique properties and wide range of applications across industries.  However, nanomaterial production is a complex process that requires a high degree of precision, making it challenging to ensure consistent quality at a large scale. Minor defects can significantly alter their functional properties and overall performance, making accurate detection of defects crucial for maintaining and controlling nanomaterial properties. To address these challenges, this project applies scan statistics to detect localized defects in scanning election microscope images of nanofibrous materials. We implemented both square and circular scanning windows of varying sizes to identify clusters …


Finite Element Methods With Anderson Acceleration And Its Application To Image Denoising, Amanda E. Diegel, Spence Hanegan, Hyeona Lim, Hoang Tran Jul 2025

Finite Element Methods With Anderson Acceleration And Its Application To Image Denoising, Amanda E. Diegel, Spence Hanegan, Hyeona Lim, Hoang Tran

Research Experiences for Undergraduates in Computational Methods with Applications in Materials Science

Image denoising is an important computational tool with applications in the medical, material science, and defense fields where CT-scans have a lot of noise that degrades quality and clearness. While there are several methods of solving image denoising problems, the one we focused on is total variation where we solve a difficult nonlinear partial differential equation that minimizes noise. There are also many numerical methods to find an approximate solution to this nonlinear partial differential equation, but the one we focus on is the finite element method. In addition, we used a fixed-point iteration method to handle the nonlinearity and …


Emancipation From Liberalism: From Afghanistan To Iran And Transatlantic Worlds. An Interview With Nivi Manchanda. (Interviewed By Bojan Savić), Bojan Savic, Nivi Manchanda Jul 2025

Emancipation From Liberalism: From Afghanistan To Iran And Transatlantic Worlds. An Interview With Nivi Manchanda. (Interviewed By Bojan Savić), Bojan Savic, Nivi Manchanda

Emancipations: A Journal of Critical Social Analysis

Nivi Manchanda discusses with Bojan Savić intersections of (post)colonial othering and liberal internationalism.


Entropy Economics And American Politics In A Multipolar World. An Interview With James K. Galbraith. (Interviewed By Lillian Cicerchia), Lillian Cicerchia, James K. Galbraith Jul 2025

Entropy Economics And American Politics In A Multipolar World. An Interview With James K. Galbraith. (Interviewed By Lillian Cicerchia), Lillian Cicerchia, James K. Galbraith

Emancipations: A Journal of Critical Social Analysis

No abstract provided.


Are We Witness To The Disintegration Of Capital’S Laws Of Motion? A Review Of Jodi Dean’S Capital’S Grave: Neofeudalism And The New Class Struggle (Verso Books, 2025), Kai Heron Jul 2025

Are We Witness To The Disintegration Of Capital’S Laws Of Motion? A Review Of Jodi Dean’S Capital’S Grave: Neofeudalism And The New Class Struggle (Verso Books, 2025), Kai Heron

Emancipations: A Journal of Critical Social Analysis

No abstract provided.


Review Of Jodi Dean, Capital’S Grave: Neofeudalism And The New Class Struggle (Verso Books, 2025), James R. Martel Jul 2025

Review Of Jodi Dean, Capital’S Grave: Neofeudalism And The New Class Struggle (Verso Books, 2025), James R. Martel

Emancipations: A Journal of Critical Social Analysis

No abstract provided.