Fatigue Testing a Mechanized Percussion Well Drilling System for Water Access in Western Africa

The Mechanized Percussion Well Drilling (MPWD) Collaboratory project seeks to design a simple mechanized well drilling system for drilling shallow water wells in Western Africa. Our client, Open Door Development (ODD), seeks to make water accessible to all in the region, but has had difficulty drilling through hard soil layers. To combat this problem, the MPWD team has worked closely with Mr. Joseph Longenecker to develop a mechanized percussion well drilling rig that is capable of drilling through these harder layers. Currently, the MPWD team is seeking to provide recommendations to improve the lifetime of our client’s new, fully mechanized rig design. This year, our team’s work has been focused specifically on analyzing the lifetime of the rig’s driveline chains and also on its frame. For the driveline chains, the team will be conducting fatigue testing on a model of the driveline system to determine which type of chain should be used on the rig. To determine the lifetime of the frame, the team will be performing a series of static, buckling, and fatigue finite element analyses on the rig’s frame. The most recent accomplishments of the MPWD team have nearly proved that their design for the loading application will be feasible for use on the actual testing rig and that multiple studies of finite element analysis can be performed to simulate the different rig frame loading scenarios.https://mosaic.messiah.edu/engr2021/1019/thumbnail.jp

Healthcare Mistreatment, State-Level Policy Protections, and Healthcare Avoidance Among Gender Minority People

Introduction: This study examined whether past experiences of mistreatment in healthcare were associated with greater healthcare avoidance due to anticipated mistreatment among gender minority (GM) people. We evaluated whether state-level healthcare policy protections moderated this relationship. Methods: Data from the 2018 Annual Questionnaire of The PRIDE Study, a national longitudinal study on sexual and gender minority people’s health, were used in these analyses. Logistic regression modeling tested relationships between lifetime healthcare mistreatment due to gender identity or expression and past-year healthcare avoidance due to anticipated mistreatment among GM participants. Interactions between lifetime healthcare mistreatment and state-level healthcare policy protections and their relationship with past-year healthcare avoidance were tested. Results: Participants reporting any lifetime healthcare mistreatment had greater odds of past-year healthcare avoidance due to anticipated mistreatment among gender expansive people (n = 1290, OR = 4.71 [CI]: 3.57–6.20), transfeminine people (n = 263, OR = 10.32 [CI]: 4.72–22.59), and transmasculine people (n = 471, OR = 3.90 [CI]: 2.50–6.13). Presence of state-level healthcare policy protections did not moderate this relationship in any study groups. Conclusions: For GM people, reporting lifetime healthcare mistreatment was associated with healthcare avoidance due to anticipated mistreatment. State-level healthcare policy protections were not a moderating factor in this relationship. Efforts to evaluate the implementation and enforcement of state-level policies are needed. Continued efforts to understand instances of and to diminish healthcare mistreatment of GM people are recommended

Minority Stress, Structural Stigma, and Physical Health among Sexual and Gender Minority Individuals: Examining the Relative Strength of the Relationships

Background: Sexual and gender minority (SGM; i.e., non-heterosexual and transgender or gender-expansive, respectively) people experience physical health disparities attributed to greater exposure to minority stress (experiences of discrimination or victimization, anticipation of discrimination or victimization, concealment of SGM status, and internalization of stigma) and structural stigma. Purpose: To examine which components of minority stress and structural stigma have the strongest relationships with physical health among SGM people. Methods: Participants (5,299 SGM people, 1,902 gender minority individuals) were from The Population Research in Identity and Disparities for Equality (PRIDE) Study. Dominance analyses estimated effect sizes showing how important each component of minority stress and structural stigma was to physical health outcomes. Results: Among cisgender sexual minority women, transmasculine individuals, American Indian or Alaskan Native SGM individuals, Asian SGM individuals, and White SGM individuals a safe current environment for SGM people had the strongest relationship with physical health. For gender-expansive individuals and Black, African American, or African SGM individuals, the safety of the environment for SGM people in which they were raised had the strongest relationship with physical health. Among transfeminine individuals, victimization experiences had the strongest relationship with physical health. Among Hispanic, Latino, or Spanish individuals, accepting current environments had the strongest relationship with physical health. Among cisgender sexual minority men prejudice/discrimination experiences had the strongest relationship with physical health. Conclusion: Safe community environments had the strongest relationships with physical health among most groups of SGM people. Increasing safety and buffering the effects of unsafe communities are important for SGM health

State-Level Policy Environments, Discrimination, and Victimization among Sexual and Gender Minority People

Legislation has been passed in some states to reduce discrimination and victimization toward sexual and gender minority people (SGM; people who are not solely heterosexual and/or whose gender identity is not equal to what is socially associated with sex assigned at birth). The purpose of these analyses is to test whether state-level policy environments are associated with past-year discrimination and victimization among SGM people. Cross-sectional data from The Population Research in Identity and Disparities for Equality (PRIDE) Study annual questionnaire (collected 2018–2019), a national study of the health of SGM adults in the USA, were used for these analyses. Measures included related to discrimination, victimization, and demographic characteristics. State-level policy environments were measured using data from the Movement Advancement Project. Logistic regression analyses evaluated state-level policy environment scores and past-year discrimination and victimization among gender identity categories. In this sample, 7044 people (gender minority n = 2530) were included. Cisgender sexual minority (odds ratio [OR] = 1.007, p = 0.041) and the gender expansive subgroup of gender minority people (OR = 1.010, p = 0.047) in states with more protective policy environments had greater odds of discrimination. The gender expansive subgroup was found to have greater odds of victimization in states with more protective policy environments (OR = 1.003, p \u3c 0.05). There was no relationship between state-level policy environments and victimization among any other study groups. SGM people may experience increased risk for discrimination and victimization despite legislative protections, posing continued risks for poor health outcomes and marginalization. Evaluation of factors (e.g., implementation strategies, systems of accountability) that influence the effectiveness of state-level polices on the reported experiences of discrimination and victimization among SGM people is needed

Systematic Overestimation of Machine Learning Performance in Neuroimaging Studies of Depression

We currently observe a disconcerting phenomenon in machine learning studies in psychiatry: While we would expect larger samples to yield better results due to the availability of more data, larger machine learning studies consistently show much weaker performance than the numerous small-scale studies. Here, we systematically investigated this effect focusing on one of the most heavily studied questions in the field, namely the classification of patients suffering from Major Depressive Disorder (MDD) and healthy controls. Drawing upon a balanced sample of $N = 1,868$ MDD patients and healthy controls from our recent international Predictive Analytics Competition (PAC), we first trained and tested a classification model on the full dataset which yielded an accuracy of 61%. Next, we mimicked the process by which researchers would draw samples of various sizes ($N=4$ to $N=150$) from the population and showed a strong risk of overestimation. Specifically, for small sample sizes ($N=20$), we observe accuracies of up to 95%. For medium sample sizes ($N=100$) accuracies up to 75% were found. Importantly, further investigation showed that sufficiently large test sets effectively protect against performance overestimation whereas larger datasets per se do not. While these results question the validity of a substantial part of the current literature, we outline the relatively low-cost remedy of larger test sets

Combining Clinical With Cognitive or Magnetic Resonance Imaging Data for Predicting Transition to Psychosis in Ultra High-Risk Patients:Data From the PACE 400 Cohort

Background: Multimodal modeling that combines biological and clinical data shows promise in predicting transition to psychosis in individuals who are at ultra-high risk. Individuals who transition to psychosis are known to have deficits at baseline in cognitive function and reductions in gray matter volume in multiple brain regions identified by magnetic resonance imaging.Methods: In this study, we used Cox proportional hazards regression models to assess the additive predictive value of each modality—cognition, cortical structure information, and the neuroanatomical measure of brain age gap—to a previously developed clinical model using functioning and duration of symptoms prior to service entry as predictors in the Personal Assessment and Crisis Evaluation (PACE) 400 cohort. The PACE 400 study is a well-characterized cohort of Australian youths who were identified as ultra-high risk of transitioning to psychosis using the Comprehensive Assessment of At Risk Mental States (CAARMS) and followed for up to 18 years; it contains clinical data (from N = 416 participants), cognitive data (n = 213), and magnetic resonance imaging cortical parameters extracted using FreeSurfer (n = 231).Results: The results showed that neuroimaging, brain age gap, and cognition added marginal predictive information to the previously developed clinical model (fraction of new information: neuroimaging 0%–12%, brain age gap 7%, cognition 0%–16%).Conclusions: In summary, adding a second modality to a clinical risk model predicting the onset of a psychotic disorder in the PACE 400 cohort showed little improvement in the fit of the model for long-term prediction of transition to psychosis

Energy-Economical Heuristically Based Control of Compass Gait Walking on Stochastically Varying Terrain

Investigation uses simulation to explore the inherent tradeoffs ofcontrolling high-speed and highly robust walking robots while minimizing energy consumption. Using a novel controller which optimizes robustness, energy economy, and speed of a simulated robot on rough terrain, the user can adjust their priorities between these three outcome measures and systematically generate a performance curveassessing the tradeoffs associated with these metrics

Overview of Phobos/Deimos Regolith Ion Sample Mission (PRISM) Concept

Far more definitive information on composition is required to resolve the question of origin for the Martian moons Phobos and Deimos. Current infrared spectra of the objects are inconclusive due to the lack of strong diagnostic features.Definitive compositional measurements of Phobos could be obtained using in-situ X-ray, gamma-ray, or neutronspectroscopy or collecting and returning samples to Earth for analysis. We have proposed, in lieu of those methods, toderive Phobos and Deimos compositional data from secondary ion mass spectrometry (SIMS) measurements by calibratingthe instrument to elemental abundance measurements made for known samples in the laboratory. We describe thePhobos/Deimos Regolith Ion Sample Mission (PRISM) concept here. PRISM utilizes a high-resolution TOF plasma composition analyzer to make SIMS measurements by observing the sputtered species from various locations of the moons' surfaces. In general, the SIMS technique and ion mass spectrometers complement and expand quadrupole mass spectrometer measurements by collecting ions that have been energized to higher energies, 50-100 eV, and making measurements at very low densities and pressures. Furthermore, because the TOF technique accepts all masses all the time,it obtains continuous measurements and does not require stepping through masses. The instrument would draw less than10 W and weigh less than 5 kg. The spacecraft, nominally a radiation-hardened 12U CubeSat, would use a low-thrust SolarElectric Propulsion system to send it on a two-year journey to Mars, where it would co-orbit with Deimos and then Phobo

Many Neglected Tropical Diseases May Have Originated in the Paleolithic or Before: New Insights from Genetics

The standard view of modern human infectious diseases is that many of them arose during the Neolithic when animals were first domesticated, or afterwards. Here we review recent genetic and molecular clock estimates that point to a much older Paleolithic origin (2.5 million years ago to 10,000 years ago) of some of these diseases. During part of this ancient period our early human ancestors were still isolated in Africa. We also discuss the need for investigations of the origin of these diseases in African primates and other animals that have been the original source of many neglected tropical diseases