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The reporting quality and transparency of orthopaedic studies using Bayesian analysis requires improvement: A systematic review
Get PDFBackground
Bayesian methods are being used more frequently in orthopaedics. To advance the use and transparent reporting of Bayesian studies, reporting guidelines have been recommended. There is currently little known about the use or applications of Bayesian analysis in orthopedics including adherence to recommended reporting guidelines. The objective is to investigate the reporting of Bayesian analysis in orthopedic surgery studies; specifically, to evaluate if these papers adhere to reporting guidelines.
Methods
We searched PUBMED to December 2nd, 2020. Two reviewers independently identified studies and full-text screening. We included studies that focused on one or more orthopaedic surgical interventions and used Bayesian methods.
Results
After full-text review, 100 articles were included. The most frequent study designs were meta-analysis or network meta-analysis (56%, 95% CI 46–65) and cohort studies (25%, 95% CI 18–34). Joint replacement was the most common subspecialty (33%, 95% CI 25–43). We found that studies infrequently reported key concepts in Bayesian analysis including, specifying the prior distribution (37–39%), justifying the prior distribution (18%), the sensitivity to different priors (7–8%), and the statistical model used (22%). In contrast, general methodological items on the checklists were largely well reported.
Conclusions
There is an opportunity to improve reporting quality and transparency of orthopaedic studies using Bayesian analysis by encouraging adherence to reporting guidelines such as ROBUST, JASP, and BayesWatch. There is an opportunity to better report prior distributions, sensitivity analyses, and the statistical models used
Mycobacterium leprae in Armadillo Tissues from Museum Collections, United States
Get PDFWe examined armadillos from museum collections in the United States using molecular assays to detect leprosy-causing bacilli. We found Mycobacterium leprae bacilli in samples from the United States, Bolivia, and Paraguay; prevalence was 14.8% in nine-banded armadillos. US isolates belonged to subtype 3I-2, suggesting long-term circulation of this genotype
Correlating physicochemical and biological properties to define critical quality attributes of a recombinant AAV vaccine candidate (Dataset)
No full textRecombinant adeno-associated viruses (rAAVs) are a preferred vector system in clinical gene transfer. A fundamental challenge to formulate and deliver rAAVs as stable and efficacious vaccines is to elucidate interrelationships between the vector’s physicochemical properties and biological potency. To this end, we evaluated an rAAV-based COVID-19 vaccine candidate which encodes the Spike antigen (AC3) and is produced by a commercially viable process. First, state-of-the-art analytical techniques were employed to determine key structural attributes of AC3 including primary and higher-order structures, particle size, empty/full capsid ratios, aggregates and multi-step thermal degradation pathway analysis. Next, several quantitative potency measures for AC3 were implemented and data were correlated with the physicochemical analyses on thermal-stressed and control samples. Results demonstrate links between decreasing AC3 physical stability profiles, in vitro transduction efficiency in a cell-based assay, and importantly, in vivo immunogenicity in a mouse model. These findings are discussed in the general context of future development of rAAV-based vaccines candidates as well as specifically for the rAAV vaccine application under study
Genetic variation in chromatin state across multiple tissues in Drosophila melanogaster
Get PDFWe use ATAC-seq to examine chromatin accessibility for four different tissues in Drosophila melanogaster: adult female brain, ovaries, and both wing and eye-antennal imaginal discs from males. Each tissue is assayed in eight different inbred strain genetic backgrounds, seven associated with a reference quality genome assembly. We develop a method for the quantile normalization of ATAC-seq fragments and test for differences in coverage among genotypes, tissues, and their interaction at 44099 peaks throughout the euchromatic genome. For the strains with reference quality genome assemblies, we correct ATAC-seq profiles for read mis-mapping due to nearby polymorphic structural variants (SVs). Comparing coverage among genotypes without accounting for SVs results in a highly elevated rate (55%) of identifying false positive differences in chromatin state between genotypes. After SV correction, we identify 1050, 30383, and 4508 regions whose peak heights are polymorphic among genotypes, among tissues, or exhibit genotype-by-tissue interactions, respectively. Finally, we identify 3988 candidate causative variants that explain at least 80% of the variance in chromatin state at nearby ATAC-seq peaks
Neoliberal Tensions in Representations of Soccer in Argentina and Brazil (2003-2016)
No full textNeoliberal Tensions explores the representations of soccer in Argentine and Brazilianfilms, novels, and television programs from 2003 to 2016. This dissertation proposes that soccer,a cultural practice that identifies both countries, can be a fruitful representational motif to tracethe political effects of neoliberalism. Understanding neoliberalism not only as a set of economicpolicies but also as an affective and ideological force, I claim that the ‘neoliberal 1990s’ continueto affect cultural production during the years of the self-proclaimed ‘anti-neoliberal’ New Leftgovernments in Argentina and Brazil. The chapters examine how neoliberal discourses shapesubjectivities affectively and ideologically, particularly around three notions: the nation, themarket, and gender. The dissertation puts into dialogue theories of representation, affect,ideology, and performance to support the close readings of cultural artifacts. By engaging thesetheories, the project ties soccer and neoliberalism together as material phenomena that affectboth the body and the mind. The approach to soccer as a representational device allows us tothink about the subjectivizing power it possesses for Argentines and Brazilians. In turn, readingsoccer in the context of ‘anti-neoliberal’ governments allows us to see the continuity ofneoliberal sensibilities beyond economic policies
Nationalist Disputes: Primers for Bilateral Cooperation? Experimental Survey Evidence from Japan
No full textHow do nationalist disputes between countries affect the foreign policy preferences ofindividuals? Nationalist disputes are often initiated when members of a state disapprove ofanother state’s behavior whether it be their foreign policy choices or over a disputed territory.Much is known about how these disputes are initiated and what economic effects they have onthe targeted state but it's unclear how these disputes affect the policy preferences of the masspublic within participating states. The conventional wisdom suggests that because of thenationalistic nature of these disputes and domestic politician’s willingness to play into themcitizens should favor more aggressive foreign policies when faced with them. I fielded a surveyexperiment in Japan where respondents were primed with a nationalist dispute that their countryis having with rival South Korea. Though this sample is proud to be Japanese and views bilateralproblems with Korea as important, they largely respond to nationalist tensions out of a desire tocooperate more with Korea rather than less. These findings challenge the conventional wisdomthat nationalism inhibits cooperation and instead suggest that individuals may potentiallyrespond to such tensions with a constructive desire to increase bilateral cooperation
Search for Weak Scale Supersymmetric Particles in Compressed Scenarios
No full textA generic search for supersymmetric particles with an emphasis on compressed scenariosis performed with √s = 13 TeV proton-proton collisions at the CMS detector using a datasample with integrated luminosity of 138 fb^{−1}. Potential supersymmetric events with initial-state-radiation recoiling against a massive invisible sparticle system are organized using theRecursive Jigsaw Reconstruction method. Events are further categorized by physics objectcounts such as jet multiplicity, lepton multiplicity, b-tags, and kinematic variables that aresensitive to generic compressed sparticle topologies. This work focuses on the following piecesof a larger analysis: the selection of leptons, their efficiency measurement and calibration,and the implementation and optimization of the data driven fit. Finally expected limits witha 95% C.L. are placed on processes that include the production of electroweakinos, sleptons,and stops
Secure Attachment, Parent-offspring Communication, and Perceived Fairness in Young Adults’ Recollections of Parental Differentiation
No full textParental differential treatment (PDT) of siblings has been linked to poor well-being of children and negative relationship experiences in the family. Explicit parent-offspring communication has been suggested to help facilitate children’s understanding of PDT. Nevertheless, few studies have examined parent-offspring communication about PDT and the justification processes of differential treatment. Guided by attachment theory and equity theory, the present study examined different aspects of parent-young-adult child communication about family inequity and the effects of secure attachment and communication on young adult children’ perceptions of fairness in the occurrence of parental differential support. In a sample 168 young adults, results showed that offspring with greater secure attachment tended to be more involved in voicing their thoughts and perceived a greater amount of parent reasoning behaviors and more positive qualities in parent-offspring communication. Among the three aspects of parent-offspring communication about parental differential support, secure attachment was positively associated with perceptions of fairness of parental different support only through the positive quality of communication. Post hoc independent samples t-test further showed that perceptions of fairness did not differ between the communication (n = 168) and non-communication (n = 99) groups. The current study also indicated that communication contextual factors such as the communication initiator, type of inequity, and timing of the conversation affected the level of perceived fairness of parental differential support. These findings suggest that secure attachment plays a critical role in promoting positive parent-offspring interactions, which in turn, fosters offspring’s justification evaluations. In the occurrence of parental differential support, the way how parents and young adult children communicate affects offspring’s perceptions of fairness
Dynamically Constrained AI-based Flight Controller and ML Aircraft Analysis
No full textAutonomous flight control has great value in alleviating workload from human pilots and enabling fully autonomous flight missions. As we move towards urban air mobility, autonomous package delivery, and the development of more advanced flight vehicles, the use of autonomous flight control will be at the center of these efforts. Machine learning (ML) and reinforcement learning (RL) are being rapidly applied across engineering disciplines and are regarded to have great potential. In this work, ML and RL methods are applied to uncrewed aircraft flight dynamics and flight control in an attempt to leverage their potential.
Flight control systems are often developed using classical methods such as proportional-integral-derivative (PID) and gain scheduling techniques. While these methods have allowed for much advancements, they have limitations such as being single-input-single-output systems requiring tuning, having high dependency to trim points and having performance limitations and non-minimum phase behavior. RL techniques enable the development of multi-input-multi-output nonlinear controllers, optimizing control actions based on user-defined reward functions. This work starts by developing a controller for airspeed and pitch angle tracking of a fixed-wing uncrewed aircraft using the deep deterministic policy gradient (DDPG) RL algorithm. The controller is developed using the linear time invariant (LTI) aircraft model while taking into account motor and servo dynamics. A reward function including multiple components limits high pitch rates to avoid rapid maneuvers and unintentional stalls. While recent research has explored the use of deep RL algorithms for fixed-wing aircraft flight control, the efforts are usually limited to simulation-based validation only and do not combine throttle and control surfaces for control. The performance of the controller developed in this work is evaluated in actual flight tests and it uses throttle and elevator commands for control.
Humans and other living creatures know how to learn from their experience and improve their skills. Aircraft flight controllers on the other hand are kept static in many cases after completion of their design. The controllers do not learn from flight experience. We tackle this problem by using a bank of collected flight data in a modified DDPG training with the goal of having an RL-based flight controller evolve using previous flight experience. The performance of the original and evolved RL controllers is then evaluated in actual flight test experiments.
Given the symbiotic relationship between the quality of the dynamic model utilized in the training environment and the performance of the RL flight controller, attention is then directed to evaluating the fidelity of the aircraft dynamic model. The quality of a dynamic model used for developing an aircraft controller has a direct impact on the quality of the developed controller. The dynamic models used in this work up to this point were developed using low-fidelity low-cost physics-based methods. A study is done to evaluate the fidelity of this physics-based model in different flight phases and the model was shown to have errors in capturing the aircraft dynamics with the correct magnitude and even had incorrect trends.
The final part of this work focuses on improving the fidelity of the aircraft model used for RL-controller development. Conventional aircraft system identification techniques offer a way to develop aircraft models with improved fidelity, but the methods can be restrictive, particularly in flight test requirements and procedures. Having no pilot onboard a UAS exacerbates this challenge. In this work, a data-driven machine learning framework is used to improve the fidelity of an aircraft model, overcoming the limitations of standard time-domain system identification methods. A bank of flight data collected from twelve flight tests was used to model the aircraft's lateral-directional dynamics using a long short-term memory (LSTM) model, known for its ability to model sequential processes. The developed model was shown to have improved performance over the physics-based models, with up to 45% improvements.
The unique contributions of this work are:
1. A longitudinal neural network controller is developed using the DDPG RL algorithm for a fixed-wing UAS while uniquely accounting for actuation dynamics and incorporating the pitch rate in the reward function to mitigate large control rates and aircraft stall. The performance of the DDPG-based flight controller was validated using multiple actual flight tests. The controller successfully controlled the aircraft in the actual flight test environment although it was trained on the low-fidelity simulation environment. The promise of generalization was assessed and the controller did not require tuning. The multi-input-multi-output mapping requirement was met and followed the reward function.
2. A mathematical framework is used to evolve a neural network flight controller based on real world experience. The framework uses previously collected flight data accrued over time and stores it in a replay buffer. This buffer is then used for evolving the flight controller using the DDPG RL algorithm. Uniquely, flight test validation verification of the work is performed.
3. Data-driven machine learning techniques are used to improve the fidelity of an aircraft lateral-directional dynamic model, overcoming the limitations of conventional system identification techniques. To assess the improvement in the aircraft model, the LSTM model developed using the bank of previously collected flight test data was used in developing an RL-based flight controller. Flight test validation verification showed that the RL-based controller outperformed other modern and adaptive control techniques even in intentional adverse onboard conditions and in tracking challenging flight paths