University of Puerto Rico at Mayagüez Institutional Repository
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Publication Open Access Caracterización fenotípica del ganado bovino criollo de Puerto Rico: Coloración(Estación Experimental Agrícola, 2025)El ganado Criollo de Puerto Rico es un recurso genético altamente adaptado a nuestras condiciones ambientales, pero probablemente en peligro de desaparecer. Por esta razón, diversos criadores y la Universidad de Puerto Rico, Recinto de Mayagüez se han unido como parte de un esfuerzo por preservar a estos animales, incluyendo la posibilidad de formar una asociación para el registro de esta raza. Para determinar cuáles animales deben ser registrados, primero es necesario caracterizar el fenotipo de esta raza. Este trabajo pretende establecer la base para la caracterización de su coloración. El ganado Criollo de Puerto Rico asume una coloración roja uniforme en todo el cuerpo, dentro de una gama de tonalidades posibles entre el rojo claro (bayo) y el rojo intenso (indio). Estos animales pueden presentar diferentes tonalidades de coloración negra en distintas partes del cuerpo incluyendo el morro, las pestañas, la piel, la borla, las patas, las pezuñas, la cara y los cuernos. Aunque poco frecuente, el ganado Criollo puede presentar manchas de color blanco, predominantemente de pequeño tamaño y localizadas en el área abdominal. También, en algunos machos puede observarse la incidencia de líneas negras en su pelaje (color gateado o “brindle”). Nuestro ganado Criollo puede asumir prácticamente cualquier combinación de estas coloraciones. La descripción de la coloración específica de cada parte del cuerpo puede usarse como una herramienta inicial para la identificación, caracterización y el posible registro de estos animales.Person Metadata only Publication Restricted Open-air 5G services testbed-study of electromagnetic interference effects on wireless sensor network using 5G technology(2026-05-08)The increasing deployment of Fifth Generation (5G) cellular infrastructure in indoor environments such as airports demands an evaluation of wireless network resilience under Radio Frequency Interference (RFI) conditions. This graduate engineering project presents the design, implementation, and experimental evaluation of a 5G-based Internet of Things (IoT) environmental monitoring node developed as part of an open-air 5G services testbed at the University of Puerto Rico at Mayagüez (UPRM) in collaboration with Collins Aerospace. The prototype integrates a Raspberry Pi (RPi) based processing unit, a Quectel RM502Q-AE 5G module operating with a commercial 5G Subscriber Identity Module (SIM), and multiple environmental sensors within a unified architecture capable of remote monitoring. Controlled RFI was introduced using calibrated signal generators under both vertical and horizontal transmitter antenna (TX) polarizations to evaluate network degradation thresholds of the IoT node, which employs mirrored slanted receiver antenna (RX) polarizations. These tests were conducted to analyze network mode transitions, latency variation, and data rate performance under defined applied signal generator power output (Pout) levels that emit RFI to the cellular network. Results demonstrate measurable differences in network stability and fallback behavior depending on polarization orientation, with defined Pout levels triggering 5G mode fallback. The findings provide insight into the susceptibility of 5G IoT systems operating in indoor environments and contribute to the development of more resilient wireless monitoring architectures.Publication Restricted Process knowledge to facilitate the implementation of continuous manufacturing within pharmaceutical industry, a focus on overcoming challenges(2026-04-28)Continuous manufacturing (CM) is a highly integrated system in which materials are continuously fed into the process and finished products are simultaneously produced with assured quality. CM offers significant advantages over batch manufacturing such as limited manual interventions, a steady-state process, consistent drug quality through controlled unit operations, flexible batch sizes, and scalable with equivalent critical quality attributes. The CM process reduces manufacturing cost, inventory, and development time, bringing high-quality medicines to patients faster. However, implementing CM demands substantial efforts, knowledge, and expertise across multiple areas. The studies focused on development of procedures and sequence of operations that support the implementation of direct compression CM in pharmaceutical industry. The studies involved powder characterization to evaluate whether the materials used were suitable for the CM process. A characterization of the feeders was performed to ensure the controlled dispensing of drug and excipients which is precursor to all other unit operation. The continuous mixing was then optimized to maximize the blend uniformity and reduce any possible variation in mass flow rate from feeders. The process analytical technology (PAT) system was implemented to ensure state of control (e.g., blend uniformity) during continuous mixing process. The studies focused on addressing the major challenges in implementation of PAT, such as design and integration of representative sampling interface, method development for routine performance checks of the NIR spectrometer, mass interrogated by NIR spectra and multivariate data analysis. The operating procedure was developed for the stream sampler to integrate within CM line to obtain representative spectra. The robustness of CM process and PAT system was evaluated during multiple independent runs on different days over six-month study period. Detailed knowledge was gained in equipment operation, powder physical properties and flow dynamics, PAT implementation, and multivariate data analysis to support the implementation of CM process.Publication Restricted Applying the multiscale model-to-model cloud comparison (M3C2) method to evaluate landslide source area metrics in Puerto Rico(2026-04-16)Landslides are a commonly occurring hazard in Puerto Rico (PR); understanding where these slope movements can happen and the amount of sediment mobilized is critical information to understand erosion and to keep track of reservoir storage capacity in PR. It is impractical to visit and measure each of the tens of thousands of landslide field sites after any given widespread landslide triggering event, thus the volume-area (V-A) scaling relationship equation helps us to better quantify these through remote sensing. This study focuses on implementing an automated method of landslide identification and volume measurement using a multiscale model to model cloud comparison (M3C2) of pre- and post-event LiDAR datasets, for rapid assessment of widespread mass-wasting sites. The study used two epoch LiDAR datasets from pre- and post-Hurricane María with a code modified from Bernard et al. (2021) to automatically perform the M3C2 change detection. Using the resulting landslide source areas point cloud, the V-A scaling relationship for four different watersheds (Lago Caonillas, Lago Dos Bocas, Lago Lucchetti, and Río Grande de Añasco) and eight distinct geological terranes were obtained. The landslide source areas identified by the M3C2 method were compared with previous manually developed landslide inventories. The M3C2 method generated a dataset of landslide source areas that were co-located with 54% of landslide sites identified in previous inventories. This reproducibility rate signifies that the automatic process is useful to identify the type of shallow landslides that are most common in PR. The M3C2 method was successfully implemented in Puerto Rico to identify 96,100 landslide source areas in the target study basins, a 2.52 times increase of what was manually identified across the four basins in the Hurricane María inventory (Hughes et al., 2019). V-A relationship comparison among the basins did not reveal significant differences from landslide inventories developed elsewhere. The overall V-A relationship for all landslide source areas identified in this study is: 𝑉=0.356∗𝐴1.076. The constants are representative of shallow mass movements as defined by Larsen (2010).
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