Coal power plants in the United States have been decommissioned at an unprecedented rate in the last decade. However, these sites can have negative impacts on the environment even after site operations have ceased, leaching toxic elements and compounds into nearby surface and groundwater. Brayton Point Power Station was one such site on the coast of Somerset, Massachusetts. Decommissioned in 2017, concentrations of the toxic elements arsenic, boron, chromium, lithium, molybdenum, and selenium, all of which are associated with coal ash leaching, were analyzed before, during, and after site closure. Using data taken from monitoring wells between 2015 and 2019, the impact of coal ash disposal at the power station was evaluated by running a test comparing concentrations in wells downgradient and upgradient of coal ash disposal sites before site closure. Then, impacts of remediation efforts were analyzed by running a test comparing concentrations before and after site closure. Finally, field samples were collected in 2023 to observe whether there were impacts on the waterways around the site. It was found that there was a statistically significant difference in concentration between upgradient and downgradient wells for all constituents except chromium and selenium, indicating that the site impacted nearby groundwater. It was also found that there wasn’t a significant difference in concentrations from the wells before and after remediation efforts, with the exception of chromium. The results of this study emphasize the continued role that legacy waste from fossil fuels has on the environment, even as greener technologies are implemented worldwide. 

At New Mexico Tech, the outreach program sends robotic combat kits to schools around the state for young students to get a taste of engineering projects and inspire the next generation of New Mexico Tech students. The MESA class of robots are sent to middle school and high school students to build, and then compete in a competition at the end of the school year. The focus of this project is to provide an additional design for the MESA robot kit that is more interesting and involved. The new design is aimed at more experienced builders that want a slightly more challenging project while still remaining similar to the original MESA robot kit and within a reasonable margin of safety. The design chosen for the new MESA kit is one with a low RPM, higher torque rotating disk weapon, which lowers the impact of a strike from the weapon while remaining powerful enough to lift another robot. The new kit has proven to be simple to assemble without power tools and remains similar to the original kit, using many of the same parts. 

Fiber-Bragg Grating (FBG) involves using optical fibers to measure strain, temperature and other parameters. This is accomplished by recording data received from a laser directed through a fiber optic cable attached to an experimental medium. An FBG cable contains sets of reflective lenses at exact spacing from each other, which will allow some light waves to pass through, while waves of the same wavelength as the spacing of the lenses will be refracted. Analysis of the light spectrum present after the cable has passed the experimental medium can provide insight into the medium. The cable is validated with experimental testing using a cantilever beam specimen, where strain gauges were installed along with the cable. The beam was subjected to incremental displacement, and strain values for the strain gauges and FBG sensor were recorded. Results from both sensors were compared and conclusions were drawn on performance of the FBG technology on strain measurements compared to conventional strain gauges. Further application of the fiber optic technology to monitoring a network of pipes will be explored. The experiment involves detection of the water flow through pipes and valves using FBGs attached on the outside of a plastic pipe and a tank collecting water from the outflow of the pipe. The potential of FBG strain sensing will be utilized to find if the sensors can detect changes in temperature and flow rate of the water. This should be possible, as both temperature and flow rate change will produce a resulting strain on the pipe. 

Jupiter is the largest planet in our solar system and the fifth one from the sun. It is a gas giant and its atmosphere is known for its characteristic banded appearance and many swirls seen all over the planet. These swirls are anticyclones and cyclones of and understanding their dynamics is important to understand the properties of Jupiter’s atmosphere. The Great Red Spot (GRS) is the largest one and the easiest one to identify on images of the planet. However, identifying some of the smaller ones is more difficult. Historically, scientists have been analyzing how these smaller systems move over time by identifying them by hand, but this process is time-consuming and somewhat subjective. To make the process of analyzing the properties of these spots more efficient, we have trained an AI model to automatically detect them on images of the planet. First, we trained our model to only identify prominent features like GRS, and other larger ovals. After that, we increased the complexity of the model to detect different features that are not so prominent. We present the results of training the model under different parameters and show how this could be used to automatically detect and track features from images with minimal human intervention. This would be very useful to extract valuable information about the evolution of these features over time from the thousands of images of the planets that are taken regularly by amateur observers. 

When learning a new human language, there are times where the grammar is incorrect or misspoken. In Computer Science, code is used to communicate with the computer; however, different computer languages have different grammar rules. When the code does not follow the grammar rules, error messages appear to the user. Oftentimes, the messages are vague and confusing for new users. The purpose for this research is to improve the error messages in Python, one of the most common computer languages. In order to analyze the errors that appear in Python, a suite of erroneous code fragments was collected and documented. The Python error messages for these fragments were compared to the error messages found in TygerJython, an improved version of Python. The errors were cross-referenced and rated on understandability, after which an ideal error message was composed. To efficiently rewrite and implement the improved error messages into a new Python implementation, the errors were categorized based on error type. Dividing the suite of errors into different categories, allows different approaches to be used in implementing messages for different kinds of errors. Once the improved error messages are implemented, they can be further tested and used in programming classrooms. When learning how to code, it is important to understand what the error message is saying without having to look up what it means and how to fix it. With this research, novice programmers can better understand error messages and fix their code. 

Cybersecurity refers to protecting computer systems, networks, and data from cyber attacks, theft, and damage. A major component of cybersecurity is staying current on the latest methods through which cyber attacks occur so they can be proactively handled. There is an immense amount of open-source news online that reports such methods, as well as the latest innovations in how to combat them. It would be helpful to have all of this information in one place. This is where spiders, also known as web crawlers, come in. A spider is a program that can pull content from different news article websites to amass a heap of information in one place. All this information is stored in a Splunk database, which has built-in tools to support analysis and research. One of the tools is a keyword search, meaning that specific types of attacks can be searched for in the massive data pool. Combine this with a date or time keyword, and it could grant an understanding of which times of the year receive the most frequent cyber attacks. For the sake of specificity, three different types of cyber attacks will be searched for alongside each month of the year. The three types of cyber attacks are ransomware, DoS, and phishing. If the time of year does prove to correlate with the frequency of cyber attacks, it will give users insight into which times they should be more careful in taking the proper precautions to reduce the risk of cyber-attacks against them. 

Neodymium (Nd) alloying has emerged as a promising strategy for enhancing the mechanical properties of Magnesium (Mg) alloys through grain refinement. In materials science, nucleation is the first step in forming a solid phase from a liquid or vapor phase during solidification or crystallization of a solid. The nucleation points formed during cooling grow outwards into an organized crystal structure measuring in the micron scale, known in general terms as a grain. The organization and size of millions of grains helps determine the mechanical properties of a material, such as hardness and strength. This study employs Molecular Dynamics (LAMMPS) simulations to investigate nucleation behavior of Mg alloyed with 5% and 0.5% atom percent Nd. From melting at 1500K, the alloy was cooled to 300K at rates of 2.5*10^11 K/s and 2.5*19^12 K/s. Nucleation phenomena observed in the simulations show a non-classical pattern, where the Nd atoms help form intermediaries in the Mg structure. Mg forms an HCP structure at room temperature in classical nucleation, but the non-classical nucleation saw the creation of multiple metastable intermediaries, shifting from icosahedral to HCP structure to FCC then settling into HCP. Future research endeavors will focus on further understanding the reasoning behind the non-classical nucleation of Mg-Nd alloys. Additionally, the possibility of alloying Mg with more abundant elements will be explored in order to mitigate the reliance on expensive rare-earth elements such as Neodymium. 

When miners become trapped due to accidents, rescue efforts require a safe and quick means of establishing communications through a compact radio frequency (RF) backscatter communication system powered by Organic Photovoltaic (OPV) cells. In such situations, a rescue drone equipped with a searchlight and the aforementioned communication system takes the lead in the assisted escape mission for miners. The drone establishes duplex communication with the miners through a battery-free, wearable transponder device. Initial experiments were conducted using an RF backscatter testbed - which utilizes both software-defined radios and OPV cells. These preliminary tests were crucial for assessing the conditions necessary for successful backscatter communication and evaluating the system's energy-harvesting performance. Findings from these experiments indicate that the device can operate battery-free, powered solely by OPV cells, even under low illuminance levels of less than 75 lux. Thermal and piezoelectric energy harvesting options are being tested to determine the feasibility of decreasing the system's cold-start time. To craft the device in a compact form, a co-design initiative was launched. This effort focused on developing a meander dipole antenna with the OPV cells, targeting a resonant frequency of 912 MHz. Simulation results obtained from ANSYS HFSS revealed significant changes in antenna impedance and S parameters yet minimal impact on the antenna's radiation pattern with the integration of the layered OPV structure. 

Compact intracloud discharges (CIDs) are a unique type of intracloud lightning, producing powerful very high frequency natural radio bursts. They emit strong electric field peaks, comparable to cloud-to-ground lightning observed from similar distances. They are more common at lower latitudes; regular tropical storms have high CID emissions even without being severe. CIDs seem to correlate positively with high convection and severe weather, though these conditions do not guarantee their occurrence. This study compares daily CID occurrence rates to ground-based weather station data and other lightning recorded by the Earth Networks Total Lightning Network for twelve days of thunderstorms using correlation (r-values). The CIDs were identified by their electric field waveshape recorded in wideband (160Hz – 5MHz). The weather station data include: temperature; humidity; dew point; pressure; wind speed, direction, and gust; solar radiation; and rainfall. The preliminary results show that CIDs correlate most strongly with other types of lightning, including positive and negative cloud-to-ground (CG+ and CG-) and positive and negative intracloud (IC+ and IC-) lightning. CG- lightning had 9 days with r-values higher than 0.6, CG+ and IC- each had 8 days, and IC+ had 6 days. CIDs show some correlation with rainfall and wind gust, direction, and speed. Rainfall had four days with r-values higher than 0.6, wind gust and direction each had two days, and wind speed had one day. Pressure may correlate negatively, with one day having an r-value of -0.7. Future work remains on utilizing CID observations to improve severe weather warning systems. 

Multidrug-resistant (MDR) Pseudomonas aeruginosa is a frequent cause of infections, especially in cystic fibrosis patients, where biofilms are already recalcitrant to antibiotic treatment. Pseudomonas aeruginosa creates thick biofilms which make treatment difficult and often ineffective. Bacteriophage (phage) therapy is a promising new treatment alternative to common antibiotics. Phages are viruses that attack bacteria without harm to humans. Because of this phages are useful in the treatment of MDR infections. A phage cocktail can be developed to combat a wide range of different variants of a pathogenic species. To create this phage cocktail novel phages were isolated from wastewater from the Socorro treatment plant. SP20 and SP21 were isolated using direct isolation on multidrug-resistant clinical strains AR245 and AR351. Of 91 MDR clinical isolates tested, 4 were susceptible only to SP20, one was susceptible only to SP21, and 25 strains were susceptible to both phages. DNA isolation and sequencing are underway to further characterize the phages by comparing genome sequences to those present in the GenBank database. 

Culverts are the pipes that convey water under the surface of a road. They are an integral and expensive part of transportation infrastructure and are an important topic of research for transportation engineers and government departments. A major factor in the longevity of a culvert is corrosion because in New Mexico 35121 of 50330 culverts are made of corrugated metal and are susceptible to corrosive effects. The purpose of this research is to correlate the corrosion levels on culverts on New Mexico Department of Transportation (NMDOT) maintained roads, with the Soil Survey Geographic Database (SSURGO) soil corrosion potential for steel. Data used for this project are part of the NM DOT Culvert Asset Management Program database, which includes culvert material, level of corrosion, and GPS location. These data were then filtered to only show the most corroded corrugated metal culverts across the state and then correlated with the SSURGO soil survey to determine if there is a strong connection to the soil corrosion potential. The soil type distribution of these highly corroded culverts were analyzed by overlaying the GPS locations with the soil survey map. It was found to contribute but the soil type is likely not the only factor contributing to the corrosion. These results are useful for the NMDOT to identify problem areas and address the problematic culverts and also provide a framework for analyzing other culvert materials and conditions. 

Laser powder bed fusion is a technique for additive manufacturing of metals in which the material is built up layer by layer. This technique is capable of producing geometries not attainable by traditional manufacturing methods. By using powdered mixtures of alloys novel compositions and microstructures of materials can be created. Understanding the mechanical properties of these materials is of particular importance as they can vary significantly from their traditionally manufactured counterparts. In this project a 50:50 mixture by weight of 10SiMg and Scalmalloy, an alloy consisting of Scandium, Aluminum, and Magnesium, has been created for tensile testing in a miniature Kolsky Bar setup. The miniature Kolsky Bar allows for the measurement of the stress–strain response of this alloy under high strain rates. Samples are prepared to the thickness of a foil and cut into a “dogbone” shape for tensile testing. Samples are tested with the tensile axis aligned with and perpendicular to the build direction to evaluate the effect of build direction on the mechanical response. This will discern if additive manufacturing of the alloy in this manner causes anisotropy, a dependence on direction, in properties such as tensile strength and strain to failure. Additionally, these results will be compared with quasistatic test results to evaluate the effect of strain rate on the mechanical response. High strain rate testing of this material will expand the understanding of properties of materials made through additive manufacturing, and the mechanical properties of this alloy. 

Neuroblastoma is a pediatric cancer caused by the rapid growth of immature nerve tissues. Neuroblastoma is responsible for 8% of all pediatric cancer cases, and 15% of pediatric cancer deaths, and has a 50% five-year survival rate. Some treatments are surgery, radiation, and chemotherapy. Commonly, chemotherapy has intense side effects so, to combat this, we are creating a prodrug using SN38, a topoisomerase 1 inhibitor, and packaging it inside lipid vehicles for drug delivery. Liposomes are utilized since they are non-toxic and highly customizable. The enhanced permeability and retention (EPR) effect is utilized for passive targeting of the liposomes, thus improving drug delivery, reducing side effects, and lowering required doses. The prodrug is synthesized in a Steglich esterification reaction that bonds phospholipid tails to the parent compound. The resulting mix is separated using thin layer chromatography (TLC) to isolate the desired prodrug. Once the prodrug is collected, Nuclear Magnetic Resonance Spectroscopy (NMR) is used to determine hydrogen counts and types. We compare the theoretical and measured NMR spectra to determine if the prodrug was successfully synthesized. The validated prodrug is used to create loaded liposomes via the thin film rehydration method with sonication and extrusion steps. Liposome size and drug incorporation are characterized using Dynamic Light Scattering (DLS) and Ultraviolet-Visible Spectroscopy (UV-Vis) respectively. The end-goal of this project is to help improve the targeting of anticancer drugs by using prodrug-loaded liposomes for chemotherapeutic treatment of pediatric neuroblastoma. 

Drive-by downloads have become one of the most popular web-based attack vectors for threat actors. Drive-by downloads are an attack made easy to implement by exploit-kits: purchased predeveloped exploits. The attack uses hidden JavaScript iFrames (embedded HTML documents) to redirect victims from infected websites to sites containing the payload delivery mechanism. Its low-skill implementation, high complexity, and ability to reliably deliver payloads make the attack a favored choice for threat actors. Current challenges surrounding the issue exist in the complexities of the attack mechanisms, notably within its obfuscated JavaScript code and purposefully hidden shellcode execution. As per the nature of web exploits, Drive-By Downloads have evolved to counteract many contemporary detection and prevention mechanisms. Due to this, a thorough investigation is necessary to understand what Drive-By Downloads have become. We propose to conduct a systematic mapping study to combat the attacks. Specifically, we developed four research questions concerning the attacks and conducted a comprehensive literature review to answer those questions and analyze the research field's latest detection and prevention methods. Over 40 prior research papers were studied to answer the questions. We found that Drive-By Download attacks are detected statically, through code analysis, or dynamically, through simulated runtime execution analysis. We found industry standards for prevention mechanisms rely on machine-specific implementations. Although Drive-By Downloads are a prevalent threat, procedures for mitigation include keeping an updated browser with possible external detection engines. For our immediate future study, we will perform lab-based experimentation to test the efficacy of various existing detection mechanisms. 

Creosote is an extremely drought tolerant, iconic Chihuahuan Desert shrub. Individual creosote shrubs act as islands of resources compared to bare soil without vegetation. Litter

accumulation under shrubs has been shown to promote moisture retention and carbon inputs, which stimulate microbial activity and nitrogen transformations, and add to overall patterns of spatial heterogeneity in these deserts. The Chihuahuan Desert’s historical precipitation pattern of “monsoonal” events from July-September are also becoming more variable in amount and timing, with unknown consequences for established shrub-soil-microbial dynamics. Here, we quantify the production and consumption of six climate relevant gases (CO 2 , CH 4 , N 2 O, NH 3 , NO and CO) from soils to: 1) assess the

impact of creosote on microbial gas flux and 2) evaluate shrub influence during prolonged drought versus an anomalously late monsoon. The role of shrubs on microbial activity was evaluated by comparing soils collected under both living and killed shrubs. The late monsoonal effect was evaluated by comparing soils collected after prolonged drought and within 1 week of a significant (~25 mm) precipitation event in October 2023. Soils were incubated in the lab under standardized conditions to control for factors other than shrub status and duration of drought. Soil-atmosphere gas flux will be presented with N transformation rates during the experiments. Incubation studies like this can shed light on microbial processes that are difficult to quantify in situ, and will inform future work to understand how shifting climate dynamics regulate soil-atmosphere exchange in desert ecosystems. 

As our technological development approaches an end to Moore’s law, it becomes increasingly necessary to find new and innovative ways to improve computational power and function, particularly in the field of mobile mechatronics. One concept that has recently entered the spotlight is analog computing. Through the use of analogous physical processes, it is possible to carry out computations more efficiently than with traditional digital methods. The reason this approach is not the current computational standard is that analog computing is imprecise and rarely produces exactly the same answer twice, which is not very conducive to most of the tasks we require from our modern computer devices.

Our research seeks to explore a potential application and solution to this problem; whereas speed and efficiency at the cost of precision is impractical for a calculator or a storage device, it is ideal for machine learning. The fast-but-fallible nature of analog computation is strongly analogous to the properties of neural interactions in biological organisms, which have been learning quickly and efficiently for nearly a billion years. We propose a system wherein an analog neural network is guided and connected by a digital evolutionary algorithm, which can be given precise and specific rules, output clear and coherent logs, and be modified on the fly for any directive or agenda. For our research we hosted the analog neural network on a KNOWM- memristor bank coupled to a python based evolutionary algorithm to control a simulated robot in a physics-enabled digital environment. 

This study presents an analysis of the air quality parameters including, carbon monoxide (CO), Carbon Dioxide (CO2) , Atmosphere Oxygen Percent (O2), particulate matter (PM 2.4, PM 10), temperature, relative humidity (RH) and barometric pressure. This data was collected over the periods 09/14/2023 to 02/08/2024 in Socorro, New Mexico on the New Mexico Institute of Mining and Technology campus. These measurements were captured using the Gas Lab Plus CM-500 series. The device was used around the campus taking various measurements at various times in the year taking indoor and outdoor measurements as well as nearby combustion sources. This data can be compared to data of that taken in Albuquerque, New Mexico taken with the same device. The results reveal a decrease of CO2 levels in the winter has transitioned from 2023 to 2024. This study contributed to the understanding of the local gas trends of Socorro as well as a greater understanding of how the CM-500 series functions and how it receives and establishes data. 

All eukaryotic cells have varying numbers of nuclear chromosome copies. Diploid cells have two copies of each chromosome, whereas polyploids have more than two copies (e.g., tetraploids=4, hexaploids=6, etc.). When differing ploidy individuals interbreed, the resulting offspring are often sterile; however, previous work in the model plant species, Arabidopsis thaliana, has shown that diploid-tetraploid matings can produce viable, fertile triploids. When self-fertilized, these triploid plants produce an “aneuploid swarm” where progeny vary extensively in their chromosomal numbers. Typically short-lived, these aneuploids can be applied to genetic mapping experiments to elucidate the genetic architecture of variable traits. In this experiment, we reciprocally crossed two genetically distinct tetraploid accessions of A. thaliana with diploids of the opposing accession (four total crosses) to produce triploid progeny. Approximately 10-15 seeds from each variant of A. thaliana were separately plated on four petri dishes containing plant-growth media. These plates were then incubated at 4ºC for ten days to simulate winter. The plated seeds were then placed under grow lights (16hr light, 8hr dark) at room temperature until they germinated. Seedlings were transferred to pots and allowed to flower. After using forceps to emasculate flowering mother plants, ~10 flowers on each plant were hand pollinated. The cross successfully produced new seeds. We hypothesize that these seeds will produce triploid plants. This will be verified by using flow cytometry. Understanding the role of varying ploidy in plants can allow us to better understand cell evolution and cytonuclear stoichiometry maintenance following whole genome duplications.