2270 research outputs found
Sort by
A TDMA Algorithm for Multi-Hop Energy Harvesting Wireless Sensor Networks
No full textWe propose a time-division multiple access (TDMA) algorithm for energy-harvesting wireless sensor networks (WSNs). The proposed algorithm supports different transmission scenarios like single-hop, dual-hop, and multi-hop. In addition to normal synchronization packets, the algorithm allows sensor nodes to synchronize with packets from a neighboring node within its communication range. These scenarios allow the proposed algorithm to perform at a greater range and similar consistency compared to other proposed algorithms. The results show comparable performance when compared to state-of-the-art algorithms. Additionally, results show that the synchronization interval depends on the clock drift rate of the hardware used, which varies across different sets of hardware
The Distribution of Common Loons (Gavia immer) Overwintering on a Freshwater Reservoir
No full textThe common loon (Gavia immer) is traditionally known to overwinter in coastal marine environments, yet little research has been conducted on those loons that overwinter on freshwater reservoirs. Lake Jocassee is a freshwater reservoir in northwest South Carolina where loons have overwinter in significant numbers. Past work has shown that these loons differ significantly in the degree of sociality. Some individuals are solitary, spending70% of their time with conspecifics. Using census data collected between 2018 and 2024, we examined patterns in the distribution of each of these three types of loons. We employed ArcView Geographic Information System software to analyze GPS location of solitary, loosely social, or strongly social individuals. We found highest loon densities were consistently within the Upper Toxaway area of the lake, with solitary loons favoring the Lower Toxaway, while strongly social loons predominantly occupied the Howard Creek arm. These findings support the hypothesis that loon distribution is influenced by lake morphology and the degree of sociality, with river mouths—rich in nutrients and assemblages of forage fish—being preferred habitats for social loons. More robust surveys of fish population assessments would facilitate our understanding of habitat selection and social behavior among overwintering loons
Exploring New Fluorophores as a Rapid Field Detection Strategy for PFAS in Soil and Water
No full textPolyfluoroalkyl substances (PFAS), more commonly known as forever chemicals, are a widespread group of environmental contaminants, commonly coming from fire fighting foams. The current detection methods for these compounds entail a long wait time and high costs. Our research uses fluorescent compounds as a means of rapid field detection for these compounds in environmental soil and water samples. Samples are combined with a solution of the fluorophore and methanol and tested both visually and by fluorometer. Through the use of fluorometry and visual testing, the presence (or absence) of significant PFAS concentrations can be determined from a fluorescence shift from green to blue light in a matter of seconds. This methodology will allow for much more time and cost effective PFAS field testing for both initial evaluation and for remediation effectiveness
Silencing The Mockingbirds: Strengthening Legal Safeguards for Defamation Cases Involving Domestic Violence Allegations
Full text linkSearching for Biosignatures in Saturn’s E Ring: A data Pipeline for Cassini’s Cosmic Dust Analyzer
No full textThe Cassini–Huygens spacecraft explored the Saturn system and neighboring bodies for 20 years. One of the on-board instruments was the Cosmic Dust Analyzer (CDA), a time-of-flight mass spectrometer designed to characterize the chemical composition of dust. Because of the potential habitability of Saturn’s moon Enceladus, biosignature compounds present in the E ring or in the Enceladus plume would be a strong indication of life. This study aims to develop a data pipeline for analysis of CDA signals, ultimately searching for biosignature compounds. Previous studies have generated the constants required to calibrate TOF to mass charge ratios using experimental data. Following calibration, filtering of signals was accomplished to identify likely impact events. Next, characteristic peaks for compounds of interest were sought in likely impact signals. If found, biosignature signals could indicate the presence of life in the Saturnian system
Assessing the impact of early initiation of physical therapy compared to prolonged bed rest on length of stay in the hospital in patients with traumatic brain injuries
No full textProblem: Traumatic brain injuries are a leading cause of disability, often resulting in prolonged hospital stays and long-term rehabilitation needs. Traditional care for patients with traumatic brain injuries is normally prolonged bed rest, which may contribute to complications such as muscle atrophy, deep vein thrombosis and bed sores.
Aim/Purpose: The purpose of this study is to assess the impact of early initiation of physical therapy compared to prolonged bed rest on the length of hospital stay in patients with moderate-to-severe traumatic brain injuries.
Methods: This study utilizes a randomized controlled trial with a two-group parallel design. Participants (aged 18-65) with moderate-to-severe traumatic brain injuries will be randomly assigned to one of two groups: early physical therapy, initiated within 48 hours of hospital admission, or standard care with physical therapy initiated after one week. Length of stay, measured in days, will be compared between the groups. The Functional Independence Measure will be used to assess mobility which will be taken at baseline and discharge. Complications, including deep vein thrombosis and pressure ulcers, will also be recorded. All data will be collected through electronic health records and standardized physical assessment tools.
Conclusion: This study has the potential to make a difference in clinical practice by providing evidence on whether early physical therapy improves patient outcomes and reduces hospital length of stay in patients with traumatic brain injuries. Findings of this study may support the development of updated rehabilitation protocols, ultimately enhancing patient recovery and reducing healthcare costs
Impact of Early Ambulation on Patient Outcomes Following Surgical Procedures
No full textAbstract
Problem: Prolonged periods of reduced physical activity negatively impact patients health and recovery process. It can lead to a decline in functional mobility, the development of deep-vein thrombosis, and respiratory complications.
Purpose: The purpose of this study is to determine whether a patient who ambulates within the first 24 hours following a surgical procedure is less at risk to develop complications than a patient who has delayed ambulation. This study aims to assess the effectiveness of early ambulation in reduction of DVT formation, respiratory infection, and weakness.
Methods: This study will use a quasi-experimental design, non-randomized controlled trial to assess the complications associated with immobility during hospitalization. The control group will consist of a retrospective chart review at previous admitted patients who received standardized care. The study will be conducted on a stepdown unit in a metro-suburban hospital. Patients aged 18 and older and who are hospitalized for at least 72 hours will be eligible for inclusion. Patients in the intervention group will receive early mobilization treatment, which will be introduced within 24 hours post-procedure, unless contraindicated. The protocol will be at least three sessions of physical activity per day. A chart review will be conducted along with patient reporting to look for occurrences of deep vein thrombosis (DVT), respiratory complications, and muscle weakness.
Conclusion: Encouraging patients to mobilize soon after surgery has been shown to enhance recovery times, improve patient outcomes, and reduce healthcare costs. Early ambulation is crucial as it can contribute to reducing post-surgery complications
How Purposeful Rounding leads to decreased falls in the hospital
No full textAbstract
Problem: Patient falls remain a significant concern in healthcare, often leading to prolonged hospital stays, injuries, and increased hospital costs. Despite the implementation of evidence-based practice to reduce fall rates, falls continue to be a huge problem for healthcare agencies. Nurse led interventions, such as intentional rounding, are emerging as a solution to ensure comprehensive patient care and safety. This highlights the need for effective, evidence-based interventions to minimize fall rates and enhance patient safety in the hospital.
Purpose: The purpose of the paper is to explore how purposeful rounding by nurses leads to lower fall rates among patients compared to standardized rounding. The study seeks to identify how intentional, purposeful interactions with patients can lead to safer outcomes.
Methods: A retrospective analysis will be conducted, tracking patient fall rates over a specific period. Intentional rounding interventions will be recorded and compared to standardized rounding. Data on patient demographics, hospital unit, and patient fall history will also be considered to assess the effect of intentional rounding on fall rates. The study aims to determine if more frequent and deliberate rounds by nursing staff correlate with a reduction in falls.
Conclusion: The findings will suggest that intentional rounding may play a key role in lowering fall rates compared to standardized rounding practices. By ensuring frequent and intentional rounds, nurses can proactively address patient needs, mitigate fall risk, and enhance patient safety
Multi-Objective Optimization of Hyperparameter Tuning
No full textHyperparameter tuning is crucial in optimizing deep learning models, often requiring a balance between computational efficiency and model performance. This research explores multi-objective optimization performance for hyperparameter tuning, focusing on the trade-off between compiling time and the resulting model accuracy. To achieve results in this research, we used the Pymoo library, a Python library used for multi-objective optimization, and its documentation in order to amend previously worked-on problems to fit our needs. A custom-made dataset was used where a default configuration of a set image classification model using simple CNNs where hyperparameters are systematically altered upon running the model, recording of the training time and resulting accuracy of the model was done. This dataset was fed into our outlined problem statement and constraints, resulting in the convergence of the research multi-objective model. This problem and our model do not converge on any specific result; hence, an outside client chooses the best-fit model for their needs. This research aims to identify multiple optimal configurations that maximize accuracy while minimizing computational cost, providing insights into efficient model training strategies. Results highlight the benefits of adaptive tuning approaches in achieving an optimal balance between performance and resource consumption
