The Effects of Gender Norms on Hiv Contraction and Treatment in the Hispanic-American Population

Human immunodeficiency virus (HIV) has received significant attention in recent years due to the stigma of having the disease and the potentially fatal prognosis. Though the virus does not discriminate between groups of people in a biological manner, certain ethnic groups in the United States suffer from higher rates of transmission and lower rates of treatment. Among these groups is the Hispanic population, which accounts for 25% of HIV cases despite comprising only 17% of the US population. HIV is transmitted through contact with blood or sexual contact with infected persons. Cultural beliefs of the Hispanic population, such as machismo and marianismo, affect sexual behavior, which in turn negatively influences the rate of HIV contraction and transmission. Here, a new method for HIV education centered around the positive reinforcement of cultural beliefs is proposed, which could potentially lower the rate of HIV contraction and increase the rate of treatment in the Hispanic population

Contrasting Biblical Themes in the Novel and Film \u3cem\u3eOne Flew Over the Cuckoo’s Nest\u3c/em\u3e

In the beginning of the novel One Flew Over the Cuckoo’s Nest, Chief Bromden and his fellow patients in the psychiatric ward of the hospital are confined in a strict environment, subject to the cruel decisions of those in control, and convinced that there is no way to escape. Renewed hope for the patients comes in the form of the newly-admitted Randle McMurphy, who serves as an advocate for the overthrow of the authoritative forces controlling the ward, specifically Nurse Ratched. As savior of the ward, McMurphy frees the patients from oppression and helps them rediscover their strengths. Clear similarities exist between the plot of the novel One Flew Over the Cuckoo’s Nest and the events leading up to Jesus’s crucifixion in the Bible; however, the film adaptation of novel reduces these profound biblical depictions to simple interactions that lack deep meaning. Though the novel is incredibly notable and complex, with abundant subtleties, the film’s omission of important biblical themes renders the movie average and superficial in comparison

CHARTING THE CHOPPY WATERS: NAVIGATING MARITIME DISPUTES IN THE SOUTH CHINA SEA

In January of 2022, the United States Department of State concluded in their Limits in the Seas study that the People’s Republic of China (PRC) has asserted unlawful maritime claims in the majority of the South China Sea.1 n Limits in the Seas, the United States called on the PRC once again to “conform its maritime claims to international law and to cease its unlawful and coercive activities in the South China Sea.”2 While the legal basis for China’s claims is hotly contested, this article seeks to navigate such unlawful and coercive activities in the region by detailing the history, the claims, and the environmental impacts of the dispute, particularly on marine life and the livelihoods of people who depend on the South China Sea for their survival. Additionally, the article analyzes military conflicts in the region and examines a few of the treaties that have resulted from the decades of disputes. Overall, this article provides a comprehensive analysis of the region, highlighting the importance of resolving the dispute in a way that protects the rights of each of the claimants and preserves the fragile marine ecosystem in the region

Genome Annotation of 3 New \u3cem\u3eRhodobacter Capsulatus\u3c/em\u3e Bacteriophages

Poster presentation abstract

Smart density: a more accurate method of measuring rural residential density for health-related research

<p>Abstract</p> <p>Background</p> <p>Studies involving the built environment have typically relied on US Census data to measure residential density. However, census geographic units are often unsuited to health-related research, especially in rural areas where development is clustered and discontinuous.</p> <p>Objective</p> <p>We evaluated the accuracy of both standard census methods and alternative GIS-based methods to measure rural density.</p> <p>Methods</p> <p>We compared residential density (units/acre) in 335 Vermont school neighborhoods using conventional census geographic units (tract, block group and block) with two GIS buffer measures: a 1-kilometer (km) circle around the school and a 1-km circle intersected with a 100-meter (m) road-network buffer. The accuracy of each method was validated against the actual residential density for each neighborhood based on the Vermont e911 database, which provides an exact geo-location for all residential structures in the state.</p> <p>Results</p> <p>Standard census measures underestimate residential density in rural areas. In addition, the degree of error is inconsistent so even the relative rank of neighborhood densities varies across census measures. Census measures explain only 61% to 66% of the variation in actual residential density. In contrast, GIS buffer measures explain approximately 90% of the variation. Combining a 1-km circle with a road-network buffer provides the closest approximation of actual residential density.</p> <p>Conclusion</p> <p>Residential density based on census units can mask clusters of development in rural areas and distort associations between residential density and health-related behaviors and outcomes. GIS-defined buffers, including a 1-km circle and a road-network buffer, can be used in conjunction with census data to obtain a more accurate measure of residential density.</p

Student Compostiton Recital

Kennesaw State University School of Music presents Student Composition Recital.https://digitalcommons.kennesaw.edu/musicprograms/1390/thumbnail.jp

Fifteen years of the Australian imaging, biomarkers and lifestyle (AIBL) study: Progress and observations from 2,359 older adults spanning the spectrum from cognitive normality to Alzheimer\u27s disease

Background: The Australian Imaging, Biomarkers and Lifestyle (AIBL) Study commenced in 2006 as a prospective study of 1,112 individuals (768 cognitively normal (CN), 133 with mild cognitive impairment (MCI), and 211 with Alzheimer\u27s disease dementia (AD)) as an \u27Inception cohort\u27 who underwent detailed ssessments every 18 months. Over the past decade, an additional 1247 subjects have been added as an \u27Enrichment cohort\u27 (as of 10 April 2019). Objective: Here we provide an overview of these Inception and Enrichment cohorts of more than 8,500 person-years of investigation. Methods: Participants underwent reassessment every 18 months including comprehensive cognitive testing, neuroimaging (magnetic resonance imaging, MRI; positron emission tomography, PET), biofluid biomarkers and lifestyle evaluations. Results: AIBL has made major contributions to the understanding of the natural history of AD, with cognitive and biological definitions of its three major stages: preclinical, prodromal and clinical. Early deployment of Aβ-amyloid and tau molecular PET imaging and the development of more sensitive and specific blood tests have facilitated the assessment of genetic and environmental factors which affect age at onset and rates of progression. Conclusion: This fifteen-year study provides a large database of highly characterized individuals with longitudinal cognitive, imaging and lifestyle data and biofluid collections, to aid in the development of interventions to delay onset, prevent or treat AD. Harmonization with similar large longitudinal cohort studies is underway to further these aims

Evaluation of individual and ensemble probabilistic forecasts of COVID-19 mortality in the United States

Short-term probabilistic forecasts of the trajectory of the COVID-19 pandemic in the United States have served as a visible and important communication channel between the scientific modeling community and both the general public and decision-makers. Forecasting models provide specific, quantitative, and evaluable predictions that inform short-term decisions such as healthcare staffing needs, school closures, and allocation of medical supplies. Starting in April 2020, the US COVID-19 Forecast Hub (https://covid19forecasthub.org/) collected, disseminated, and synthesized tens of millions of specific predictions from more than 90 different academic, industry, and independent research groups. A multimodel ensemble forecast that combined predictions from dozens of groups every week provided the most consistently accurate probabilistic forecasts of incident deaths due to COVID-19 at the state and national level from April 2020 through October 2021. The performance of 27 individual models that submitted complete forecasts of COVID-19 deaths consistently throughout this year showed high variability in forecast skill across time, geospatial units, and forecast horizons. Two-thirds of the models evaluated showed better accuracy than a naïve baseline model. Forecast accuracy degraded as models made predictions further into the future, with probabilistic error at a 20-wk horizon three to five times larger than when predicting at a 1-wk horizon. This project underscores the role that collaboration and active coordination between governmental public-health agencies, academic modeling teams, and industry partners can play in developing modern modeling capabilities to support local, state, and federal response to outbreaks

The United States COVID-19 Forecast Hub dataset

Academic researchers, government agencies, industry groups, and individuals have produced forecasts at an unprecedented scale during the COVID-19 pandemic. To leverage these forecasts, the United States Centers for Disease Control and Prevention (CDC) partnered with an academic research lab at the University of Massachusetts Amherst to create the US COVID-19 Forecast Hub. Launched in April 2020, the Forecast Hub is a dataset with point and probabilistic forecasts of incident cases, incident hospitalizations, incident deaths, and cumulative deaths due to COVID-19 at county, state, and national, levels in the United States. Included forecasts represent a variety of modeling approaches, data sources, and assumptions regarding the spread of COVID-19. The goal of this dataset is to establish a standardized and comparable set of short-term forecasts from modeling teams. These data can be used to develop ensemble models, communicate forecasts to the public, create visualizations, compare models, and inform policies regarding COVID-19 mitigation. These open-source data are available via download from GitHub, through an online API, and through R packages

Finishing the euchromatic sequence of the human genome

The sequence of the human genome encodes the genetic instructions for human physiology, as well as rich information about human evolution. In 2001, the International Human Genome Sequencing Consortium reported a draft sequence of the euchromatic portion of the human genome. Since then, the international collaboration has worked to convert this draft into a genome sequence with high accuracy and nearly complete coverage. Here, we report the result of this finishing process. The current genome sequence (Build 35) contains 2.85 billion nucleotides interrupted by only 341 gaps. It covers ∼99% of the euchromatic genome and is accurate to an error rate of ∼1 event per 100,000 bases. Many of the remaining euchromatic gaps are associated with segmental duplications and will require focused work with new methods. The near-complete sequence, the first for a vertebrate, greatly improves the precision of biological analyses of the human genome including studies of gene number, birth and death. Notably, the human enome seems to encode only 20,000-25,000 protein-coding genes. The genome sequence reported here should serve as a firm foundation for biomedical research in the decades ahead