Life in Hampton Roads Report: The Tenth Annual Life in Hampton Roads Survey

[From the Executive Summary] The Social Science Research Center (SSRC) at Old Dominion University recently completed data collection for the tenth annual Life in Hampton Roads (LIHR) telephone survey. The purpose of the survey was to gain insight into residents’ perceptions of the quality of life in Hampton Roads. As in previous years, the project also investigated attitudes and perceptions of citizens regarding topics of local interest such as transportation and traffic, perceptions of police, health, community, education, work, experiences with flooding, and other issues. These are presented independently or as trending with previous years when appropriate. This year, the SSRC also partnered with the city of Chesapeake who provided additional questions for the survey. The SSRC completed interviews with 882 Hampton Roads residents via landline and cell phones

Life in Hampton Roads Report: The 13th Annual Life in Hampton Roads Survey

[From the Executive Summary] The Social Science Research Center (SSRC) at Old Dominion University is pleased to present the results from the 13th annual Life in Hampton Roads (LIHR) survey. The purpose of the survey was to gain insight into residents’ perceptions of the quality of life in Hampton Roads. This year, all survey data was collected via telephone interviews as was the case prior to the pandemic. More than two-thirds of respondents rated the quality of life in the region as excellent or good (69.3%). About 25% rated Hampton Roads’ quality of life as fair (24.7%) and 4.5% rated it as poor. Consistent with previous years, respondents rated the quality of life in their city and their neighborhood higher than they did for the region as a whole. Just over 70% rated the quality of life in their city as good or excellent (70.1%) and 24.2% rated their city as fair. Only 5.6% rated their city’s quality of life as poor. Neighborhood ratings of quality of life remain the highest, with 82.3% rating their neighborhood as excellent or good. Only 15.9% rated their neighborhood quality of life as fair and 1.8% rated it as poor

Life in Hampton Roads Report: The 12th Annual Life in Hampton Roads Survey

[From the Executive Summary] The Social Science Research Center (SSRC) at Old Dominion University is pleased to present the results from the 12th annual Life in Hampton Roads (LIHR) survey. The purpose of the survey was to gain insight into residents’ perceptions of the quality of life in Hampton Roads. It is important to note that the methodology for this year’s survey differs from previous Life in Hampton Roads surveys. The first ten years of the survey were conducted using a random sample of Hampton Roads residents via telephone. Last year state and university COVID-19 restrictions did not allow for staffing of the SSRC call center during the survey period. Therefore, on-line survey panels were used to solicit respondents to complete a web-based survey. This year, a mixed methods approach of telephone calls and web surveys were used to administer the survey. Given the continued and evolving pandemic conditions in Hampton Roads and the rest of the world, many of this year’s questions focused on residents’ experiences with and responses to continuing COVID-19 conditions

Life in Hampton Roads Report: The 11th Annual Life in Hampton Roads Survey

[From the Executive Summary] The Social Science Research Center (SSRC) at Old Dominion University is pleased to present the results from the 11th annual Life in Hampton Roads (LIHR) survey. The purpose of the survey was to gain insight into residents’ perceptions of the quality of life in Hampton Roads. It is important to note that the methodology for this year’s survey differs from previous Life in Hampton Roads surveys. The first ten years of the survey were conducted using a random sample of Hampton Roads residents via telephone. However, this year state and university COVID-19 restrictions did not allow for staffing of the SSRC call center during the survey period. Therefore, on-line survey panels were used to solicit respondents to complete a web-based survey. Given the pandemic conditions in Hampton Roads and the rest of the world, many of this year’s questions focused on residents’ experiences with and responses to COVID-19 conditions

Seabasing and joint expeditionary logistics

Student Integrated ProjectIncludes supplementary material. Executive Summary and Presentation.Recent conflicts such as Operation Desert Shield/Storm and Operation Iraqi Freedom highlight the logistics difficulties the United States faces by relying on foreign access and infrastructure and large supply stockpiles ashore to support expeditionary operations. The Navy's transformational vision for the future, Sea Power 21, involves Seabasing as a way to address these difficulties by projecting and sustaining joint forces globally from the sea. This study analyzes logistics flow to, within and from a Sea Base to an objective, and the architectures and systems needed to rapidly deploy and sustain a brigade-size force. Utilizing the Joint Capabilities Integration and Development System (JCIDS), this study incorporates a systems engineering framework to examine current systems, programs of record and proposed systems out to the year 2025. Several capability gaps that hamper a brigade-size force from seizing the initiative anywhere in the world within a 10-day period point to a need for dedicated lift assets, such as high-speed surface ships or lighter-than-air ships, to facilitate the rapid formation of the Sea Base. Additionally, the study identifies the need for large-payload/high-speed or load-once/direct-to- objective connector capabilities to minimize the number of at-sea transfers required to employ such a force from the Sea Base in 10 hrs. With these gaps addressed, the Joint Expeditionary Brigade is supportable from the Sea Base.http://archive.org/details/seabasingndjoint109456918N

Predictive power of deep-learning segmentation based prognostication model in non-small cell lung cancer

PurposeThe study aims to create a model to predict survival outcomes for non-small cell lung cancer (NSCLC) after treatment with stereotactic body radiotherapy (SBRT) using deep-learning segmentation based prognostication (DESEP).MethodsThe DESEP model was trained using imaging from 108 patients with NSCLC with various clinical stages and treatment histories. The model generated predictions based on unsupervised features learned by a deep-segmentation network from computed tomography imaging to categorize patients into high and low risk groups for overall survival (DESEP-predicted-OS), disease specific survival (DESEP-predicted-DSS), and local progression free survival (DESEP-predicted-LPFS). Serial assessments were also performed using auto-segmentation based volumetric RECISTv1.1 and computer-based unidimensional RECISTv1.1 patients was performed.ResultsThere was a concordance between the DESEP-predicted-LPFS risk category and manually calculated RECISTv1.1 (φ=0.544, p=0.001). Neither the auto-segmentation based volumetric RECISTv1.1 nor the computer-based unidimensional RECISTv1.1 correlated with manual RECISTv1.1 (p=0.081 and p=0.144, respectively). While manual RECISTv1.1 correlated with LPFS (HR=6.97,3.51-13.85, c=0.70, p<0.001), it could not provide insight regarding DSS (p=0.942) or OS (p=0.662). In contrast, the DESEP-predicted methods were predictive of LPFS (HR=3.58, 1.66-7.18, c=0.60, p<0.001), OS (HR=6.31, 3.65-10.93, c=0.71, p<0.001) and DSS (HR=9.25, 4.50-19.02, c=0.69, p<0.001). The promising results of the DESEP model were reproduced for the independent, external datasets of Stanford University, classifying survival and ‘dead’ group in their Kaplan-Meyer curves (p = 0.019).ConclusionDeep-learning segmentation based prognostication can predict LPFS as well as OS, and DSS after SBRT for NSCLC. It can be used in conjunction with current standard of care, manual RECISTv1.1 to provide additional insights regarding DSS and OS in NSCLC patients receiving SBRT.SummaryWhile current standard of care, manual RECISTv1.1 correlated with local progression free survival (LPFS) (HR=6.97,3.51-13.85, c=0.70, p<0.001), it could not provide insight regarding disease specific survival (DSS) (p=0.942) or overall survival (OS) (p=0.662). In contrast, the deep-learning segmentation based prognostication (DESEP)-predicted methods were predictive of LPFS (HR=3.58, 1.66-7.18, c=0.60, p<0.001), OS (HR=6.31, 3.65-10.93, c=0.71, p<0.001) and DSS (HR=9.25, 4.50-19.02, c=0.69, p<0.001). DESEP can be used in conjunction with current standard of care, manual RECISTv1.1 to provide additional insights regarding DSS and OS in NSCLC patients

Decreased Openness to Experience Is Associated with Migraine-Type Headaches in Subjects with Lifetime Depression

Migraine and depression frequently occur as comorbid conditions, and it has been hypothesized that migraine with and without depression may have a different genetic background. A distinct personality trait constellation has been described in migraineurs. Less attention, however, was paid to personality differences in migraineurs with and without depression which may also shed light on differences in the neurobiological, background. The aim of our study was to investigate big five personality traits, headaches, and lifetime depression (DEP) in a large European general population sample. METHODS: Relationship between DEP, Big Five Inventory personality traits, and headaches identified by the ID-Migraine Questionnaire were investigated in 3,026 individuals from Budapest and Manchester with multivariate and logistic regression analyses. RESULTS: Both DEP and migraine(ID) showed differences in personality traits. Neuroticism was an independent risk factor for both conditions while a significant interaction effect appeared between the two in the case of openness. Namely, subjects with migraine(ID) and without DEP scored higher on openness compared to those who had depression. CONCLUSION: While we confirmed previous results that high neuroticism is a risk factor for both depression and migraine, openness to experience was significantly lower in the co-occurrence of migraine and depression. Our results suggest that increased openness, possibly manifested in optimal or advantageous cognitive processing of pain experience in migraine may decrease the risk of co-occurrence of depression and migraine and thus may provide valuable insight for newer prevention and intervention approaches in the treatment of these conditions

Generalised Anxiety Disorder – A Twin Study of Genetic Architecture, Genome-Wide Association and Differential Gene Expression

Generalised Anxiety Disorder (GAD) is a common anxiety-related diagnosis, affecting approximately 5% of the adult population. One characteristic of GAD is a high degree of anxiety sensitivity (AS), a personality trait which describes the fear of arousal-related sensations. Here we present a genome-wide association study of AS using a cohort of 730 MZ and DZ female twins. The GWAS showed a significant association for a variant within the RBFOX1 gene. A heritability analysis of the same cohort also confirmed a significant genetic component with h2 of 0.42. Additionally, a subset of the cohort (25 MZ twins discordant for AS) was studied for evidence of differential expression using RNA-seq data. Significant differential expression of two exons with the ITM2B gene within the discordant MZ subset was observed, a finding that was replicated in an independent cohort. While previous research has shown that anxiety has a high comorbidity with a variety of psychiatric and neurodegenerative disorders, our analysis suggests a novel etiology specific to AS