Making friends in online games: gender differences and designing for greater social connectedness

ABSTRACT

While online multiplayer games provide an opportunity for players to both maintain and establish new connections, male and female players have been found to experience these environments differently. Interviews (n?=?22) and focus groups (n?=?14) were used to explore these differences as they impact on creating new social connections, as well as to provide recommendations for the development of new social tools and features that account for these differences. While all participants experienced toxicity and performance pressure as barriers to forming new connections, female players uniquely reported the impacts of misogynistic targeting and stereotype threat. In turn, female players wishing to avoid these stresses would often mask their gender. The common practice of gender misrepresentation by both male and female players impacted female players’ ability to create social connections through voice technology, as well as building their distrust of unknown others. Recommendations are made to build social connectedness between players taking into account the specific constraints faced by female players. These include establishing mentoring opportunities as well as profiling players beyond their immediate skill or rank. Additionally, the desire for control of one’s online identity presents practical challenges that may be overcome through thoughtful design.     

Neurotropic RNA Virus Modulation of Immune Responses within the Central Nervous System

The central nervous system (CNS) necessitates intricately coordinated immune responses to prevent neurological disease. However, the emergence of viruses capable of entering the CNS and infecting neurons threatens this delicate balance. Our CNS is protected from foreign invaders and excess solutes by a semipermeable barrier of endothelial cells called the blood–brain barrier. Thereby, viruses have implemented several strategies to bypass this protective layer and modulate immune responses within the CNS. In this review, we outline these immune regulatory mechanisms and provide perspectives on future questions in this rapidly expanding field.     

Effect of steam cooking on distribution of paralytic shellfish toxins in different tissue compartments of scallops Patinopecten yessoensis

This study investigated the effect of steam cooking on distribution of paralytic shellfish poisoning toxins (PSP-toxins) in scallops Patinopecten yessoensis. Toxins analysis by high-performance liquid chromatography showed that most of the PSP-toxins (>70%) were accumulated in viscera and adductor muscle of the raw scallops. Steam cooking induced significant loss (p < 0.05) of PSP-toxins from viscera (16%), adductor muscle (24%), gill and mantle (11%) while 32% of the toxins were retained inside viscera and adductor muscle. Overall, 51% of PSP-toxins leaked out from scallop tissues during steam cooking. However, there was no significant loss (p > 0.05) of PSP-toxins from gonad. Consumption of viscera was the most significant risk factor for causing PSP, while gonad and scallop soup were the second most significant. A rapid PSP test further verified detectable levels of PSP-toxins in all samples. However, possible interfering substance(s) in adductor muscles and gonads might potentially affect the results from this test.     

A nurse practitioner intervention model to maximize efficient use of telemetry resources

BACKGROUND: Telemetry monitoring is widely used in hospitals; the importance of being able to monitor and examine dysrhythmias has been universally accepted. Yet it is often used for patients who do not actually require this technology. A model to improve the efficiency of telemetry use entailed the use of an advanced practice nurse (APN; identical to a nurse practitioner) to provide concurrent review and intervention of floating telemetry, which is available for patients independently of the floor location and who do not need an intensive care unit bed. ADDRESSING OVERUSE: The demand for floating telemetry at Hackensack University Medical Center had equaled or exceeded the telemetry availability virtually 100% of the time, even after local guidelines had been disseminated in 1998. The APN carried out concurrent monitoring and intervened with the attending physician when patients were on telemetry for longer than 48 hours and did not meet the local telemetry guidelines. RESULTS: The mean number (standard error [SE]) of hours per patient declined from 65.2 +/- 0.7 hours (95% confidence interval, 63.8 to 66.6 hours) for the 11 months before the intervention to a mean of 49.6 +/- 0.4 hours (95% confidence interval, 48.7 to 50.2 hours) for the 29 months after intervention--representing a decrease of 34% (p < 0.0001). This decrease led to an increase in the number of patients per month put on telemetry. DISCUSSION: The APN model, an aggressive approach that induced change almost immediately, was then applied to other quality improvement projects.     

Goodness-of-fit tests for logistic regression models when data are collected using a complex sampling design

Logistic regression models are frequently used in epidemiological studies for estimating associations that demographic, behavioral, and risk factor variables have on a dichotomous outcome, such as disease being present versus absent. After the coefficients in a logistic regression model have been estimated, goodness-of-fit of the resulting model should be examined, particularly if the purpose of the model is to estimate probabilities of event occurrences. While various goodness-of-fit tests have been proposed, the properties of these tests have been studied under the assumption that observations selected were independent and identically distributed. Increasingly, epidemiologists are using large-scale sample survey data when fitting logistic regression models, such as the National Health Interview Survey or the National Health and Nutrition Examination Survey. Unfortunately, for such situations no goodness-of-fit testing procedures have been developed or implemented in available software. To address this problem, goodness-of-fit tests for logistic regression models when data are collected using complex sampling designs are proposed. Properties of the proposed tests were examined using extensive simulation studies and results were compared to traditional goodness-of-fit tests. A Stata ado function svylogitgof for estimating the F-adjusted mean residual test after svylogit fit is available at the author's website http://www.people.vcu.edu/~kjarcher/Research/Data.htm.     

Key attributes of the SAPHIRE risk and reliability analysis software for risk-informed probabilistic applications

The Idaho National Laboratory is a primary developer of probabilistic risk and reliability analysis (PRRA) tools, dating back over 35 years. Evolving from mainframe-based software, the current state-of-the-practice has led to the creation of the SAPHIRE software. Currently, agencies such as the Nuclear Regulatory Commission, the National Aeronautics and Aerospace Agency, the Department of Energy, and the Department of Defense use version 7 of the SAPHIRE software for many of their risk-informed activities. In order to better understand and appreciate the power of software as part of risk-informed applications, we need to recall that our current analysis methods and solution methods have built upon pioneering work done 30–40 years ago. We contrast this work with the current capabilities in the SAPHIRE analysis package. As part of this discussion, we provide information for both the typical features and special analysis capabilities, which are available. We also present the application and results typically found with state-of-the-practice PRRA models. By providing both a high-level and detailed look at the SAPHIRE software, we give a snapshot in time for the current use of software tools in a risk-informed decision arena.     

A comparative study of the reliability of nine statistical software packages

The reliabilities of nine software packages commonly used in performing statistical analysis are assessed and compared. The (American) National Institute of Standards and Technology (NIST) data sets are used to evaluate the performance of these software packages with regard to univariate summary statistics, one-way ANOVA, linear regression, and nonlinear regression. Previous research has examined various versions of these software packages using the NIST data sets, but typically with fewer software packages than used in this study. This study provides insight into a relative comparison of a wide variety of software packages including two free statistical software packages, basic and advanced statistical software packages, and the popular Excel package. Substantive improvements from previous software reliability assessments are noted. Plots of principal components of a measure of the correct number of significant digits reveal how these packages tend to cluster for ANOVA and nonlinear regression.     

Combining ground-based measurements and MODIS-based spectral vegetation indices to track biomass accumulation in post-fire chaparral

Multi-temporal satellite imagery can provide valuable information on the patterns of vegetation growth over large spatial extents and long time periods, but corresponding ground-referenced biomass information is often difficult to acquire, especially at an annual scale. In this study, we test the relationship between annual biomass estimated using shrub growth rings and metrics of seasonal growth derived from Moderate Resolution Imaging Spectroradiometer (MODIS) spectral vegetation indices (SVIs) for a small area of southern California chaparral to evaluate the potential for mapping biomass at larger spatial extents. These SVIs are related to the fraction of photosynthetically active radiation absorbed by the plant canopy, which varies throughout the growing season and is correlated with net primary productivity. The site had most recently burned in 2002, and annual biomass accumulation measurements were available from years 5 to 11 post-fire. We tested the metrics of seasonal growth using six SVIs: normalized difference vegetation index (NDVI), enhanced vegetation index (EVI), soil adjusted vegetation index (SAVI), normalized difference water index (NDWI), normalized difference infrared index 6 (NDII6), and vegetation atmospherically resistant index (VARI). Several of the seasonal growth metrics/SVI combinations exhibit a very strong relationship with annual biomass, and all SVIs show a strong relationship with annual biomass (R² for base value time series metric ranging from 0.45 to 0.89). Although additional research is required to determine which of these metrics and SVIs are the most promising over larger spatial extents, this approach shows potential for mapping early post-fire biomass accumulation in chaparral at regional scales.     

Antimicrobial activity of Yerba Mate (Ilex paraguariensis) aqueous extracts against Escherichia coli O157:H7 and Staphylococcus aureus

Abstract: Bioactive compounds from natural plant sources are becoming increasingly important to the food industry. Ilex paraguariensis is used in the preparation of a widely popular tea beverage (Yerba Mate) in the countries of Uruguay, Paraguay, Argentina, and Brazil. In this study, extracts of 4 brands of commercial tea, derived from the holly plant species, Ilex paraguariensis, were evaluated for their ability to inhibit or inactivate bacterial foodborne pathogens. The ultimate goal was to evaluate potential use of the extracts in commercial applications. Dialyzed aqueous extracts were screened for antimicrobial activity against Escherichia coli O157:H7 and Staphylococcus aureus. S. aureus was found to be the more sensitive to extracts than E. coli O157:H7. Minimum bactericidal concentrations (MBCs) were determined to be approximately 150 to 800 μg/mL and 25 to 50 μg/mL against E. coli O157:H7 and S. aureus, respectively. A Uruguayan brand had reduced activity against E. coli O157:H7 compared to the Argentinean brands tested. It was concluded that Yerba Mate could be used as a potential antimicrobial in foods and beverages against these pathogenic bacteria. Practical Application: Soluble extracts from Yerba Mate are natural antimicrobials that can be incorporated into food products to achieve longer shelf life.