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Background: Risk of anal squamous cell carcinoma (anal cancer) is greater among men who have sex with men (MSM) living with human immunodeficiency virus (HIV). We describe the frequency of and factors associated with abnormal anal cytology results in Colombian MSM living with HIV. Methods: This retrospective observational cohort study included MSM ≥18 years old living with HIV screened with anal cytology at Hospital Universitario San Ignacio in Bogotá, Colombia between January 2019 and February 2020. A multivariable log-binomial regression model estimated associations with abnormal anal cytology. Results: A total of 211 patients were included. Mean age was 35.6 years. Sixty-eight (32.3%) had an abnormal anal cytology result: ASC-US 33.8% ( n = 23); LSIL 60.3% ( n = 41); and HSIL 5.9% ( n = 4). MSM with an STI diagnosis in the previous 12 months (RR 1.48, [95% CI 1.03–2.12], p = 0.032) or with a CD4+ T cell count Conclusions: These data provide crucial information to guide scale up of anal cancer screening at select centers in Colombia. Our results also suggest STI prevention efforts and improved virological control among MSM living with HIV may have the secondary benefit of reducing the risk of anal cancer.

The COVID-19 pandemic of 2020 arose during the presidential primary process and spring elections for states across the U.S. One of the consequences of the pandemic on election administration was th...

The use of vote by mail was an important topic during the 2020 election cycle. This election coincided with the most significant public health crisis in the United States in a century, combined wit...

Racial identification is a critical factor in understanding a multitude of important outcomes in many fields. However, inferring an individual’s race from ecological data is prone to bias and error. This process was only recently improved via Bayesian improved surname geocoding (BISG). With surname and geographic-based demographic data, it is possible to more accurately estimate individual racial identification than ever before. However, the level of geography used in this process varies widely. Whereas some existing work makes use of geocoding to place individuals in precise census blocks, a substantial portion either skips geocoding altogether or relies on estimation using surname or county-level analyses. Presently, the trade-offs of such variation are unknown. In this letter, we quantify those trade-offs through a validation of BISG on Georgia’s voter file using both geocoded and nongeocoded processes and introduce a new level of geography—ZIP codes—to this method. We find that when estimating the racial identification of White and Black voters, nongeocoded ZIP code-based estimates are acceptable alternatives. However, census blocks provide the most accurate estimations when imputing racial identification for Asian and Hispanic voters. Our results document the most efficient means to sequentially conduct BISG analysis to maximize racial identification estimation while simultaneously minimizing data missingness and bias.

BACKGROUND Gay, bisexual, and other men who have sex with men (MSM) with higher perceived risk of HIV are more aware of and willing to use pre-exposure prophylaxis (PrEP). PrEP is an effective HIV prevention strategy, but there is a lack of data on how PrEP use might moderate the relationship between sexual behavior and perceived risk of HIV. Moreover, most studies have measured perceived risk of HIV via a single question. OBJECTIVE We estimated the moderating effect of PrEP use on the relationship between sexual behavior and perceived risk of HIV, measured with the 8-item Perceived Risk of HIV Scale (PRHS), among Brazilian MSM. METHODS A cross-sectional, online survey was completed by Brazilian Hornet app users >18 years old between February-March 2020. This analysis includes data from cisgender men who reported sex with men in the previous six months. We evaluated the moderating effect of current PrEP use on the relationship between sexual behavior, measured via the HIV Incidence Risk Index for MSM (HIRI-MSM), and perceived risk of HIV, measured by the PRHS. Higher HIRI-MSM (range 0-45) and PRHS scores (range 10-40) indicate greater behavioral risk and perceived risk of HIV, respectively. Both were standardized to z-scores for use in multivariable linear regression models. RESULTS Among 4,344 cisgender MSM, 448 (10.3%) were currently taking PrEP. Current PrEP users had a higher mean HIRI-MSM score (21.0 vs. 13.2, p CONCLUSIONS Our results suggest current PrEP users have confidence in PrEP’s effectiveness as an HIV prevention strategy. PrEP’s effectiveness, its positive psychological impact, and the frequent HIV testing and interaction with health services required of PrEP users may jointly influence the relationship between sexual behavior and perceived risk of HIV among PrEP users.

In this article, we investigate the college teaching experiences of four first-generation and working-class (FGWC) sociology educators with varying social locations. We used collaborative autoethnography to compare our backgrounds and university navigational strategies employed and shared with our students and mentees. Using an intersectional lens, we find our experiences reflect both commonalities and divergences in the FGWC experience, including disclosure of our FG and/or WC origin status to students and our perceptions of how race, gender, and parental status shape our teaching of sociology across differing institutional settings. We end by using insights gleaned from comparing our experiences to provide recommendations for creating more inclusive classroom and institutional environments.

For the past several decades, political scientists have sought to understand the impact of legislative redistricting and gerrymandering on a variety of outcomes. However, traditional metrics such as compactness scores and newer metrics such as aggregated simulations impose very strong assumptions that make their use difficult. In this study, we propose a new graphical framework for analyzing districts that relaxes current assumptions while allowing analysts to focus on the choices that redistricting parties may potentially make. We then leverage the newest advances in district simulation algorithms to extend this framework to propose four new metrics. These new metrics are Edge-Cut Growth (ECG), Excess Edge (EE), and Edge per District Gain (EDG), and Internal Boundary Growth (IBG). These new metrics are then compared to several existing metrics, allowing us to test the attributes that our approach is similar to. In doing so, we demonstrate that the four new metrics are best seen as theoretical and technical advances on current metrics that focus on district geometry.

It has long been noted that electing members of the U.S. House of Representatives in single-member, mutually exclusive districts often leads to discrepancies between the partisanship of the elector...

Women in medicine have made progress since Elizabeth Blackwell: the first women to receive her medical degree in the United States in 1849. Yet although women currently represent just over one-half of medical school applicants and matriculates, they continue to face many challenges that hinder them from entering residency, achieving leadership positions that exhibit final decision-making and budgetary power, and, in academic medicine, being promoted. Challenges include gender bias in promotion, salary inequity, professional isolation, bullying, sexual harassment, and lack of recognition, all of which lead to higher rates of attrition and burnout in women physicians. These challenges are even greater for women from groups that have historically been marginalized and excluded, in all aspects of their career and especially in achieving leadership positions. It is important to note that, in several studies, it was indicated that women physicians are more likely to adhere to clinical guidelines, provide preventive care and psychosocial counseling, and spend more time with their patients than their male peers. Additionally, some studies reveal improved clinical outcomes with women physicians. Therefore, it is critical for health care systems to promote workforce diversity in medicine and support women physicians in their career development and success and their wellness from early to late career.

Using data from a variety of public opinion sources, we explore changes in trust in the vote count. A historic gap in confidence between Democrats and Republicans has grown, caused by two reasons: (1) an unusually big increase in Democratic confidence coupled with a modest decrease in Republican confidence and (2) a pre-election trust gap that already placed Democrats more confident than Republicans. Looking at confidence that votes in one’s state were counted as intended, there is a sharp discontinuity in Republican responses at the 50% point in Trump two-party vote share. In addition, Republicans in states Trump lost were much less confident when more votes were cast by mail.

Recently, the use of vote-by-mail has been increasing in popularity, with Washington, Colorado, and Hawaii moving exclusively to mail-based election systems. While election reformers tout the various benefits of this change, what impact does mail voting have on voter confidence? I seek to answer this by by leveraging the implementation of postal voting in Washington and Colorado through the use of the Survey of the Performance of American Elections (SPAE) dataset, along with difference-in-differences design, genetic matching, Mahalanobis distance matching, and ordinal logistic regression analysis. In doing so, I demonstrate that the implementation of vote by mail causes a significant decrease in voter confidence in both states. However, this decrease appears to be temporary, disappearing after only single election cycle. These results shed light on the potential impact of recent expansions of convenience voting in the United States, while also furthering the debate around perceptions of electoral integrity in democratic systems.

In the 2018 election, the Democratic Party rode a midterm wave to win a majority in the US House of Representatives. Throughout the campaign and its aftermath, a great deal of attention has been paid to the effects of gerrymandering, sorting, and district boundaries on the outcome of House races. We assess the impact of current district boundaries on electoral outcomes, using actual election results from 2018 alongside those generated by a simulation technique that relies upon advanced geographic information systems (GIS) and principles of graph theory. We find that redistricting practices in Republican-drawn states were at least partially effective in stemming the blue wave, allowing them to hold more seats than we would otherwise expect. Finally, we demonstrate that the insulating properties of Republican redistricting efforts also impacted the makeup of state legislatures, which could impact House redistricting in 2020.

In the past decade, debate around the effects of the instant runoff voting (IRV) has intensified, as proponents seek to build upon a victory in Maine to expand its use to more states. However, there has relied on unsubstantiated claims from both sides, as it has only been used in a single statewide election. This lack of information around IRV is compounded by the fact that relatively little work has been done around the behavioral impacts of IRV in a multi- party setting, with most of the elections happening in cities that lean strongly Democrat. This study seeks to better understand this reform by being the first to holistically analyze both the micro-level and macro-level impacts of IRV. In doing so, I find strong experimental and observational evidence to suggest that the negative impacts of IRV outweigh any positive effects, and that elite-led opinion may serve as a mitigating factor.

For the past several decades, political scientists have sought to understand the impact of legislative redistricting and gerrymandering on a variety of outcomes. However, traditional metrics such as compactness scores and newer metrics such as aggregated simulations impose very strong assumptions that make their use difficult. In this study, we propose a new graphical framework for analyzing districts that relaxes current assumptions while allowing analysts to focus on the choices that redistricting parties may potentially make. We then leverage the newest advances in district simulation algorithms to extend this framework to propose four new metrics. These new metrics are Edge Cut Growth (ECG), Excess Edge (EE), and Edge per District Gain (EDG), and Internal Boundary Growth (IBG). These new metrics are then compared to several existing metrics, allowing us to test the attributes that our approach is similar to. In doing so, we demonstrate that the four new metrics are best seen as theoretical and technical advances on current metrics that focus on district geometry.

This paper introduces a method to integrate target behavior into the multiple hypothesis tracker (MHT) likelihood ratio. In particular, a periodic track appraisal based on behavior is introduced. The track appraisal uses elementary topological data analysis coupled with basic machine-learning techniques, and it adjusts the traditional kinematic data association likelihood (i.e., track score) using an established formulation for feature-aided data association. The proposed method is tested and demonstrated on synthetic vehicular data representing an urban traffic scene generated by the Simulation of Urban Mobility package. The vehicles in the scene exhibit different driving behaviors. The proposed method distinguishes those behaviors and shows improved data association decisions relative to a conventional, kinematic MHT.

In the 2016 U.S. General Election, agents of the Russian Federation attempted to influence the election through a multi-faceted campaign, which included the spread of of fake news as well as cyber attacks on campaigns, individuals, and even electoral infrastructure. Elite reaction was swift. Unlike on most issues, however, elites in the Republican Party remain divided. Leveraging this rare and enduring intra-party disagreement in today's age of polarized parties, we are able to begin to understand how people react to conflicting elite cues that are free from usual partisan considerations. This enables us to present a theory of elite-led opinion formation that includes intra-party polarization, expanding on the current literature. We theorize that in a scenario where there is a divided party and a unified party, those who identify with the unified party will form crystallized opinions that are reflective of those held by party elites. Members of the divided party will have perceive conflicting elite cues, and form opinions that are more malleable and susceptible to change from future elite cues. We test this theory by examining the impact of salience of Russian hacking as well as different levels in elite cohesion on belief that Russian hacking actually took place heading into the 2018 election. This is carried out through a two-pronged approach, leveraging a nationally-representative online survey (N=1000) and two survey experiments. We find that different levels of elite agreement on Russian hacking, rather than the information about Russian hacking itself, caused respondents to update their perceptions of Russian hacking. This finding is particularly strong for the Republican subsample in our experiment. We also find strong evidence that supporters of Trump are resistant to information, going as far as to demonstrate the opposite effect when presented with information that directly contradicts the President's position. Furthermore, we find similar results regarding elite influence on opinion for trade policy, a much less salient issue in comparison to Russian hacking. In doing so, we not only provide new evidence on the impact of disourse around Russian hacking, but add to a growing literature on elite discourse to include intra-party discourse and attachment to groups of the elites within a single party.

© 2018 Authors. The integration of social robots within service industries requires social robots to be persuasive. We conducted a vignette experiment to investigate the persuasiveness of a human, robot, and an information kiosk when offering consumers a restaurant recommendation. We found that embodiment type significantly affects the persuasiveness of the agent, but only when using a specific recommendation sentence. These preliminary results suggest that human-like features of an agent may serve to boost persuasion in recommendation systems. However, the extent of the effect is determined by the nature of the given recommendation.

© 2018 ACM. Robots interacting with humans in public spaces often need to collect users' private information in order to provide the required services. Current privacy legislation in major jurisdictions requires organisations to disclose information about their data collection process and obtain user's consent prior to collecting privacy sensitive information. In this study, we consider a privacy-sensitive design of a data collection system for face identification. We deployed a face enrolment system on a humanoid robot with human-like gesturing and speech. We compared it with an equivalent system, in terms of capability and interactive process, on a screen-based interactive kiosk. In our previous contribution, we investigated the effects that embodiment has on users' privacy considerations. We found that an embodied humanoid robot is capable of collecting more private information from users in comparison to a disembodied interactive kiosk. However, this effect was statistically significant only when the two compared systems were using a transparent interface, i.e. an interface communicating to users the privacy policies for data processing and storage. Thus, in this work, we aim to further investigate the effects of transparency on users' privacy considerations and their experience with robot applications. We found that when comparing a non-transparent vs. transparent interface within the same system (i.e. on an embodied robot or on a disembodied kiosk) transparency does not lead to significant effects on users' privacy considerations. However, we found that transparency leads to a significantly better user experience for both systems. Therefore, our overall analyses suggest that both the interactive robot and the interactive kiosk are capable of enhancing the user experience by providing transparent information to users, which is required by privacy legislation. However, an interactive kiosk providing transparent information elicits significantly more privacy concerns in users as compared to the robot supplying the very same transparent information. This exploratory study provides conclusions that provide valuable insights for designing robot applications dealing with users privacy and it discusses the related legal implications, concluding with recommendations for privacy policymakers.

Active communication between robots and humans is essential for effective human-robot interaction. To accomplish this objective, Cloud Robotics (CR) was introduced to make robots enhance their capabilities. It enables robots to perform extensive computations in the cloud by sharing their outcomes. Outcomes include maps, images, processing power, data, activities, and other robot resources. But due to the colossal growth of data and traffic, CR suffers from serious latency issues. Therefore, it is unlikely to scale a large number of robots particularly in human-robot interaction scenarios, where responsiveness is paramount. Furthermore, other issues related to security such as privacy breaches and ransomware attacks can increase. To address these problems, in this paper, we have envisioned the next generation of social robotic architectures based on Fog Robotics (FR) that inherits the strengths of Fog Computing to augment the future social robotic systems. These new architectures can escalate the dexterity of robots by shoving the data closer to the robot. Additionally, they can ensure that human-robot interaction is more responsive by resolving the problems of CR. Moreover, experimental results are further discussed by considering a scenario of FR and latency as a primary factor comparing to CR models., Comment: 17th IEEE International Symposium on Network Computing and Applications (NCA 2018), Cambridge, USA

Sisi-Nubi (SNB) is a gas field located 25 km offshore from the modern Mahakam delta with overpressure reservoirs being found typically in the Sisi Main Zone (SMZ) interval. SNB 3D seismic data indicates a velocity reversal in the SMZ interval, where the overpressure occurs. This velocity reversal has a relation with location of shelf break (distal area), where beyond shelf break the NTG value is sharply decreased. In the Mahakam area, overpressure gas reservoirs are one of the main issues in terms of drilling hazards. This has been historically managed by integrating surrounding wells' pressure data to predict the pore pressure profile that would be expected in an upcoming well. In new areas or where pressure data is lacking, it is difficult to predict the PP which can result either in heavier than necessary well architectures or an increased risk of taking a kick. An integrated pore pressure study has been carried out on the SNB field in order to provide three dimensional and spatially continuous pore pressure prediction using four different disciplines: sedimentology, reservoir geology, geophysics and geomechanics. The integrated pore pressure model over SNB is contained within a 3D geological model where the Eaton equation can be run using following datasets: sonic well data and sedimentological trend (Well Driven model), upscaled/resampled seismic interval velocity (seismic driven model) and hybrid method as compromise between two data sources involves using the seismic data as a soft trend for the extrapolated well data (hybrid model). Based on the blind well test analysis, the hybrid methodology shows the best result in terms of precision and 3D distribution and allows a continuous prediction of pore pressures even where there is poor well control. However, the others two methodologies could be used as an alternative when the available data is limited. This methodology gives a new approach with more integrated information in 3D pore pressure modeling that improved the classic pore pressure prediction in field Scale and/or basin scale. However, with the remaining uncertainty and discrepancy between the DT well scale velocity and the DT seismic velocity, and considering all detail well events important inputs (Gas evolution including long connection tests, kick, pressure test, HC bouyancy and other drilling events), collaboration with a strong 1D Pore Pressure synthesis will give a comprehensive result.

Sisi and Nubi (SNB) fields are two adjacent primarily gas fields located 25 km offshore from the modern Mahakam delta These fields are complex from a reservoir management point of view with hundred thousands of Static & dynamic data, and continuously increase by time. Reservoir synthesis and geomodel update are always on-going process with numerous QC, data mining & data manipulation. In brief, Sisi Nubi data management & synthesis challenges are: (1) Enormous size of static & dynamic data (2) Numerous Data mining & data manipulation (3) Rigorous Geomodel QC and reporting. Business Intelligence (BI) is the philosophy of this study; it is a set of techniques and tools for the acquisition and transformation of raw data into meaningful and useful information for business analysis purposes. The goal of BI is to allow for the easy interpretation of these large volumes of data. The Sisi Nubi dashboard is a self-service business intelligence tool that was design by the asset to answer & streamline the database management and reporting, hence give more time for the asset's geosciences team to do the reservoir synthesis and optimize the study time by automate the data mining & manipulations. The Sisi Nubi dashboards composed of an automated workflow in the geomodeling platform for the data mining, combined with spreadsheet based tool for the data manipulation and presentation (dashboard-ing). The result of this study presented in 6 unique dashboards, representing 6 difference perspectives of the user. These dashboards are linked to the SNB geomodel and allow instantenous update. Combined with the updated SNB geomodel workflow, the collaboration of two tools has proven significantly streamline the geomodeling reporting & synthesis efficiency.

The argument that U.S. House districts have become more demographically homogenous over time—either through intentional gerrymandering, geographic self-sorting, or some combination of the two— is a central component of most explanations of the growth of partisan polarization in Congress. In recent research, we developed a highly sophisticated method of creating simulated, randomized districts in all states with more than one member of the House (see Powell, Clark, and Dube 2015, 2016). In this paper we build on that prior research to examine the extent to which geographic self-sorting may or may not account for trends in district homogeneity. To do so, we compare the homogeneity of actual districts as drawn to repeated iterations of randomized, simulated districts within each state. We extend this analysis to examine changes in the margins of victory in these districts. Thus, this paper presents a thorough examination of the hypothesis that geographic self-sorting (or intentional gerrymandering) is creating safer House seats and a more polarized legislative environment in Congress.

© 2017, Springer International Publishing AG. As social robots move from the laboratory into public settings the possibility of unwanted intrusion into a user’s personal privacy is magnified. The actual social interaction between human and robot may involve anthropomorphising of the robot by the user, and this may prompt the user to disclose private or sensitive information. To comprehend possible impacts we conducted an exploratory study with a novel privacy measure to understand changes to users’ privacy considerations when interacting with an embodied robotic system vs a disembodied system. In this paper we measure the difference in personal information provided to such systems, and discuss the idea that embodiment may increase users’ risk tolerance and reduce their privacy concerns.

© Springer International Publishing AG 2016. For social robots, learning from an ordinary user should be socially appealing. Unfortunately, machine learning demands an enormous amount of human data, and a prolonged interactive teaching session becomes anti-social. We have addressed this problem in the context of reward shaping for reinforcement learning. For efficient reward shaping, a continuous stream of rewards is expected from the teacher. We present a simple framework which seeks rewards for a small number of steps from each of a large number of human teachers. Therefore, it simplifies the job of an individual teacher. The framework was tested with online crowd workers on a transport puzzle. We thoroughly analyzed the quality of the learned policies and crowd’s teaching behavior. Our results showed that nearly perfect policies can be learned using this framework. The framework was generally acceptable in the crowd’s opinion.

Chemosynthetic ecosystems teeming with tubeworm colonies were discovered at hydrothermal vents in the Galapagos Ridge in 1977 and at cold seeps at the base of the Florida Escarpment in 1984. As a result of these reports a number of fossil examples were identified in the rock record. One such assemblage was recognized in the Western Interior Seaway, in the Middle Campanian Pierre Shale Formation, where previous researchers noted siboglinid (formerly vestimentiferan and pogonophoran) tubeworms in methane-derived nodular limestones with tubules. On the inside these tubules have an outer ring of micrite with microparticulate siliciclastic materials and a core of calcite cement. Alternatively, they have an outer annulus of calcite cement and a core of microparticulate siliciclastic materials with calcite cements. Interestingly, the cemented cores can contain meniscate and vesiculate fabrics in association with the microparticulate linings. With this evidence we infer that the tubules preserve fabrics of former gas bubbles; the microparticulate linings are deposits that accumulated on the walls of the tubules as fluids streamed through them. Methane bubbles would have carried adhered siliciclastic microparticles and bubble wakes would have held entrained microparticles. We, thus, interpret the tubules to be former, small, subseafloor conduits along which fluid and particulate transport occurred. Particle transport by gas bubbles is a well-known process in chemical and mineral industries. Our observations highlight this process for the first time in an ancient geologic conduit system and provide a mechanism for maintaining particulate plumes that accompany effusing methane streams at modern seeps and vents.

A complex three-dimensional quantitative image of an extended zinc oxide crystal has been obtained using Bragg coherent diffraction imaging integrated with ptychography., A complex three-dimensional quantitative image of an extended zinc oxide (ZnO) crystal has been obtained using Bragg coherent diffraction imaging integrated with ptychography. By scanning a 2.5 µm-long arm of a ZnO tetrapod across a 1.3 µm X-ray beam with fine step sizes while measuring a three-dimensional diffraction pattern at each scan spot, the three-dimensional electron density and projected displacement field of the entire crystal were recovered. The simultaneously reconstructed complex wavefront of the illumination combined with its coherence properties determined by a partial coherence analysis implemented in the reconstruction process provide a comprehensive characterization of the incident X-ray beam.

The context for foreclosure prevention and mitigation hinges critically upon whether a state operates in a judicial or nonjudicial regime. Nonjudicial foreclosure regimes allow mortgage lenders to foreclose on homes without substantial court supervision. In these states, the time from the borrower receiving an initial notice of foreclosure to the date of the completed foreclosure sale tends to be substantially shorter than in states with judicial foreclosure systems. Moreover, nonjudicial foreclosure regimes tend to offer borrowers fewer legal protections and make it more difficult for homeowners to slow or intervene in the routine foreclosure process. For example, many of the more well-known efforts to reduce foreclosures, including mediation programs in which lenders must meet with borrowers in the presence of a mediator, have occurred in judicial states. This report examines legislation affecting the mortgage foreclosure process adopted in states with nonjudicial foreclosure processes from January 2005 through May of 2010. Little is known about how policymakers in nonjudicial states have responded to the foreclosure crisis. In general, borrowers in nonjudicial states are at a significant disadvantage when compared to those in judicial states and, short of changing to a judicial foreclosure regime, efforts to reduce foreclosures run up against a different set of constraints and challenges. The primary purpose of this report is to understand how policymakers in nonjudicial states have attempted to respond in terms of legislative modifications to the foreclosure process in the face of the national foreclosure crisis. We do this by analyzing state legislative activity during the study period. In particular we identified all legislation enacted during this period that concerns the regulation and administration of the default and foreclosure process for single-family residential mortgages. We quantify and classify this legislation, and identify states that were relatively active in this area during the study period. We then focus on eight of the most active states, describing some of the key provisions adopted in these states.