Addressing Health Disparities Among Homeless in Alachua County through Community-Based Participatory Research.

Introduction. In states such as Florida that did not expand Medicaid, a large number of economically disadvantaged individuals do not qualify for subsidies to buy health insurance through the Affordable Care Act (ACA) 2. This leaves the health needs of Florida’s homeless population largely unaddressed. Nearly 48.1% of Alachua County’s homeless population has disabling conditions 16. This confirms a pressing need to understand the homeless population\u27s healthcare needs, knowledge, and barriers in accessing healthcare. Methods. We used a Community-Based Participatory Research model in conducting health fairs and needs assessment surveys, incentivizing participation, and providing education about existing resources. The surveys were conducted at two homeless meal service sites and consisted of 22 questions regarding access to healthcare, utilization, and satisfaction. Health fairs consisted of blood pressure, blood glucose, and mental health screening. Patient participation was encouraged through games, prizes and food. Results. Of the population we surveyed, 100% have income levels below $11,490, therefore all uninsured fall into the ACA coverage gap. Those less than 65 years of age do not qualify for Medicare unless disabled. Some qualify for Medicaid as shown in tables. Fifty-eight percent were uninsured and did not get any treatment for their illnesses. Additionally, 67% had no knowledge of free local healthcare clinics. Discussion/Conclusion. The majority of this population falls into the ACA Coverage Gap, lacks knowledge about free community clinics, and inappropriately uses the ED. Future implications of this research involve advocacy to expand Medicaid in Florida and enroll those who are eligible for health insurance. Vital goals include outreach by free healthcare clinics to make healthcare more accessible, as well as building trust with the community through continued outreach initiatives. A community-Based Participatory Research Model is an effective tool to increasing collaboration among diverse members of the community in order to bring meaningful and positive change to the health of populations

A multi-robot educational and research framework

Robots have greatly transformed human’s life. Multi-disciplinary research in robotics essentially demands having sophisticated frameworks with diverse range of capabilities ranging from simple tasks like testing of control algorithms to handling complex scenarios like multiple robot coordination. The present research addresses this demand by proposing a reliable, versatile and cheap platform enriched with enormous features. The framework has been conceptualized with three robots having different drive mechanisms, sensing and communication capabilities. The proposed ‘Wanderbot’ family consists of ForkerBot, MasterBot and HexaBot. The ForkerBot is a four-wheeled robot equipped with ultra sonic range finder, wheel encoder, bump sensor, temperature sensor, GSM, GPS and RF communication modules. The robot, having a payload capacity of 8 pounds, supports both Differential and Ackerman drive mechanisms and can be used to validate advanced obstacle avoidance algorithms. The MasterBot is also a wheeled robot with an on-board camera and is skid-steered. The robot finds potential in research on image processing and computer vision and in analysis and validation of algorithms requiring high-level computations like complex path traversal. The third member in the Wander family, HexaBot, is a six-legged robot, which is able to exhibit the movement of tripod gait and can be used for investigating walking and climbing algorithms. The three members of Wander family can communicate with one another, thus making it a good candidate for research on coordinated multi-robots. Additionally, such a prototyped platform with vast attractive features finds potential in an academic and vocational environment

Are gluon showers inside a quark-gluon plasma strongly coupled? a theorist's test

We study whether in-medium showers of high-energy gluons can be treated as a sequence of individual splitting processes $g{\to}gg$, or whether there is significant quantum overlap between where one splitting ends and the next begins. Accounting for the Landau-Pomeranchuk-Migdal (LPM) effect, we calculate such overlap effects to leading order in high-energy $\alpha_{\rm s}(\mu)$ for the simplest theoretical situation. We investigate a measure of overlap effects that is independent of physics that can be absorbed into an effective value $\hat q_{\rm eff}$ of the jet-quenching parameter $\hat q$.Comment: 6 pages, 3 figures. Main change for v3: minor clarifications adde

HEXOSYS II - Towards realization of light mass robotics for the hand

This research presents a prototype of a direct-driven, optimized and light-mass hand exoskeleton that is designed to fit over the dorsal side of the hand, thus retaining palm free for interaction with real/virtual objects. The link lengths of the proposed Hand EXOskeleton SYStem (HEXOSYS) TT have been selected based on an optimization algorithm. In an attempt to make the design human hand compatible, the actuators of HEXOSYS II have been chosen as a result of series of experiments on human hands of various sizes. The system based on an optimum under-actuated mechanism provides 3 DOF/finger. The resultant motion of the exoskeleton allows the wearer to perform flexion/abduction as well as passive abduction/adduction. Simple and under-actuated mechanisms together with compact mechanical design lead to realize a light mass robotic system. The first prototype of HEXOSYS II has been fabricated. Comprising of four fingers, which are enough to accomplish most of our daily life activities, the system weighs 600 grams. © 2011 IEEE

Optimal set of EEG features for emotional state classification and trajectory visualization in Parkinson's disease

In addition to classic motor signs and symptoms, individuals with Parkinson's disease (PD) are characterized by emotional deficits. Ongoing brain activity can be recorded by electroencephalograph (EEG) to discover the links between emotional states and brain activity. This study utilized machine-learning algorithms to categorize emotional states in PD patients compared with healthy controls (HC) using EEG. Twenty non-demented PD patients and 20 healthy age-, gender-, and education level-matched controls viewed happiness, sadness, fear, anger, surprise, and disgust emotional stimuli while fourteen-channel EEG was being recorded. Multimodal stimulus (combination of audio and visual) was used to evoke the emotions. To classify the EEG-based emotional states and visualize the changes of emotional states over time, this paper compares four kinds of EEG features for emotional state classification and proposes an approach to track the trajectory of emotion changes with manifold learning. From the experimental results using our EEG data set, we found that (a) bispectrum feature is superior to other three kinds of features, namely power spectrum, wavelet packet and nonlinear dynamical analysis; (b) higher frequency bands (alpha, beta and gamma) play a more important role in emotion activities than lower frequency bands (delta and theta) in both groups and; (c) the trajectory of emotion changes can be visualized by reducing subject-independent features with manifold learning. This provides a promising way of implementing visualization of patient's emotional state in real time and leads to a practical system for noninvasive assessment of the emotional impairments associated with neurological disorders

Early Outcome of Coronary Artery Bypass Grafting in Obese and Non Obese Patients

Objective: To determine the impact of body mass index (BMI) on short-term outcomes like; renal failure, prolonged ventilation and mortality after CABG surgery. Methodology: This prospective comparative study was conducted at the Cardiac Surgery Department, Pervaiz Elahi Institute of Cardiology, Bahawalpur from February to December 2021. A total of 148 patients were enrolled after taking written consent and data was collected through predesign proforma sheets, including; clinical history, investigation and early outcomes in term of (renal failure, prolonged ventilation, and mortality). SPSS 23 was used to analyze data with statistically significant p-value < 0.05. Results: The findings showed that average age of research participants were 57.14 ± 3.07 (age range 30-73 years) and 121 (81.76%) male compared with 27(18.24%) female patients were enrolled with insignificant p-value of 0.730. In this study prolonged ventilation was found in 5(6.76%) obese and 8(10.81%) non-obese patients with insignificant p-value of 0.070. Renal Failure was found in 2 (2.70%) obese and 8 (10.81%) non-obese patients with significant p-value of 0.02 and mortality in 4(5.41%) obese and 2 (2.70%) non-obese patients with significant p-value of 0.0482. Conclusion: The results of the current investigation demonstrated that an obese BMI was a reliable indicator of morbidity or mortality following CABG

Identification and analysis of free games\u27 permissions in Google Play

© 2015 IEEE. Smart phones are becoming more prevalent than ever, and so does the use of game applications for mobile phones. Android platform offers an attractive environment for game developers, as it is open source and it is supported by many of the available smart phones. This paper surveys, analyses, and identifies the most requested permissions when installing a new game application on Android. We base on this analysis to draw some conclusions and recommendations about how to recognize suspicious games or malware. The study focuses on Android free game applications and covers 530 games from Google Play. The study shows that \u27full Internet access\u27 is the most requested permission and that 60% of the requested permissions are of high risk. These results clearly call for more vigilance when installing new games/applications and mandate new solutions to secure Android applications and help end-users choose their games/applications safely

SIM Card Forensics: Digital Evidence

With the rapid evolution of the smartphone industry, mobile device forensics has become essential in cybercrime investigation. Currently, evidence forensically-retrieved from a mobile device is in the form of call logs, contacts, and SMSs; a mobile forensic investigator should also be aware of the vast amount of user data and network information that are stored in the mobile SIM card such as ICCID, IMSI, and ADN. The aim of this study is to test various forensic tools to effectively gather critical evidence stored on the SIM card. In the first set of experiments, we compare the selected forensic tools in terms of retrieving specific data; in the second set, genuine user data from eight different SIM cards is extracted and analyzed. The experimental results on a real-life dataset support the effectiveness of the SIM card forensics approach presented in this paper. Keywords: SIM card, Digital Forensics, Forensic tools, ICCID, IMS

On the analysis of EEG power, frequency and asymmetry in Parkinson's disease during emotion processing

Objective: While Parkinson’s disease (PD) has traditionally been described as a movement disorder, there is growing evidence of disruption in emotion information processing associated with the disease. The aim of this study was to investigate whether there are specific electroencephalographic (EEG) characteristics that discriminate PD patients and normal controls during emotion information processing. Method: EEG recordings from 14 scalp sites were collected from 20 PD patients and 30 age-matched normal controls. Multimodal (audio-visual) stimuli were presented to evoke specific targeted emotional states such as happiness, sadness, fear, anger, surprise and disgust. Absolute and relative power, frequency and asymmetry measures derived from spectrally analyzed EEGs were subjected to repeated ANOVA measures for group comparisons as well as to discriminate function analysis to examine their utility as classification indices. In addition, subjective ratings were obtained for the used emotional stimuli. Results: Behaviorally, PD patients showed no impairments in emotion recognition as measured by subjective ratings. Compared with normal controls, PD patients evidenced smaller overall relative delta, theta, alpha and beta power, and at bilateral anterior regions smaller absolute theta, alpha, and beta power and higher mean total spectrum frequency across different emotional states. Inter-hemispheric theta, alpha, and beta power asymmetry index differences were noted, with controls exhibiting greater right than left hemisphere activation. Whereas intra-hemispheric alpha power asymmetry reduction was exhibited in patients bilaterally at all regions. Discriminant analysis correctly classified 95.0% of the patients and controls during emotional stimuli. Conclusion: These distributed spectral powers in different frequency bands might provide meaningful information about emotional processing in PD patients