Toward a General Framework of Biased Reasoning: Coherence-Based Reasoning.

A considerable amount of experimental research has been devoted to uncovering biased forms of reasoning. Notwithstanding the richness and overall empirical soundness of the bias research, the field can be described as disjointed, incomplete, and undertheorized. In this article, we seek to address this disconnect by offering "coherence-based reasoning" as a parsimonious theoretical framework that explains a sizable number of important deviations from normative forms of reasoning. Represented in connectionist networks and processed through constraint-satisfaction processing, coherence-based reasoning serves as a ubiquitous, essential, and overwhelmingly adaptive apparatus in people's mental toolbox. This adaptive process, however, can readily be overrun by bias when the network is dominated by nodes or links that are incorrect, overweighted, or otherwise nonnormative. We apply this framework to explain a variety of well-established biased forms of reasoning, including confirmation bias, the halo effect, stereotype spillovers, hindsight bias, motivated reasoning, emotion-driven reasoning, ideological reasoning, and more.

Test Structure Design for Defect Detection during Active Thermal Cycling.

Integrated power ICs acting as smart power switches for automotive or industrial applications are often subjected to active thermal cycling. Consequently, they undergo significant self-heating and are prone to various failure mechanisms related to the electro-thermo-mechanical phenomena that take place in the device metallization. In this article a test structure consisting of a lateral DMOS transistor equipped with several integrated sensors is proposed for metallization fatigue assessment. The design of the test structure is presented in detail, alongside with design considerations drawn from the literature and from simulation results. The testing procedure is then described, and experimental results are discussed. The experimental data provided by the integrated sensors correlated with the electro-thermal simulation results indicate the emergence of a failure mechanism and this is later confirmed by failure analysis. Conclusions are further drawn regarding the feasibility of using the proposed integrated sensors for monitoring defects in power ICs.

Early evaluation of a powered transfemoral prosthesis with force-modulated impedance control and energy regeneration.

Individuals with an above-knee (AK) amputation typically use passive prostheses, whether reactive (microprocessor) or purely mechanical. Though sufficient for walking, these solutions lack the positive power generation observed in able-bodied individuals. Active (powered) prostheses can provide positive power but suffer complex control and limited energy storage capacities. These shortcomings motivate the development of an active prosthesis implementing a novel impedance controller design with energy regeneration. The controller requires only five tuning parameters that are intuitive to adjust in contrast to the current standard-finite state machine impedance scheduling of up to 45 gains. This simplification is uniquely achieved by modulating knee joint impedance by axial shank force. Furthermore, the proposed control approach introduces analytical guidance for impedance tuning to purposely integrate energy regeneration; specifically, a precise amount of negative damping is injected into the joint. A pilot study conducted with a volunteer with an AK amputation walking at three distinct speeds and at continually self-selected varying speeds demonstrated the adaptability of the controller to changes in speed. Self-powered operation was attained for all trials despite low mechanical component efficiencies. These early results suggest the efficacy of simplifying impedance control tuning and fusing control and energy regeneration in transfemoral prostheses.

A Generalized Unscented Transformation for Probability Distributions.

The unscented transform uses a weighted set of samples called sigma points to propagate the means and covariances of nonlinear transformations of random variables. However, unscented transforms developed using either the Gaussian assumption or a minimum set of sigma points typically fall short when the random variable is not Gaussian distributed and the nonlinearities are substantial. In this paper, we develop the generalized unscented transform (GenUT), which uses 2n+1 sigma points to accurately capture up to the diagonal components of the skewness and kurtosis tensors of most probability distributions. Constraints can be analytically enforced on the sigma points while guaranteeing at least second-order accuracy. The GenUT uses the same number of sigma points as the original unscented transform while also being applicable to non-Gaussian distributions, including the assimilation of observations in the modeling of infectious diseases such as coronavirus (SARS-CoV-2) causing COVID-19.

Interviewing for a PI position-the pandemic way.

JCB asks early career researchers to share their experience interviewing for academic faculty positions and becoming independent PIs during the COVID-19 pandemic.

Starting a lab during the COVID-19 pandemic.

JCB asks early career investigators to share their experience launching a lab during the COVID-19 pandemic.

Starting and Operating a Public Cardiac Catheterization Laboratory in a Low Resource Setting: The Eight-Year Story of the Uganda Heart Institute Catheter Laboratory.

Background: Low- and-middle-income-countries (LMICs) currently bear 80% of the world's cardiovascular disease (CVD) mortality burden. The same countries are underequipped to handle the disease burden due to critical shortage of resources. Functional cardiac catheterization laboratories (cath labs) are central in the diagnosis and management of CVDs. Yet, most LMICs, including Uganda, fall remarkably below the minimum recommended standards of cath lab:population ratio due to a host of factors including the start-up and recurring costs. Objectives: To review the performance, challenges and solutions employed, lessons learned, and projections for the future for a single cath lab that has been serving the Ugandan population of 40 million people in the past eight years. Methods: A retrospective review of the Uganda Heart Institute cath lab clinical database from 15 February 2012 to 31 December 2019 was performed. Results: In the initial two years, this cath lab was dependent on skills transfer camps by visiting expert teams, but currently, Ugandan resident specialists independently operate this lab. 3,542 adult and pediatric procedures were conducted in 8 years, including coronary angiograms and percutaneous coronary interventions, device implantations, valvuloplasties, and cardiac defect closures, among others. There was a consistent expansion of the spectrum of procedures conducted in this cath lab each year. The initial lack of technical expertise and sourcing for equipment, as well as the continual need for sundries present(ed) major roadblocks. Government support and leveraging existing multi-level collaborations has provided a platform for several solutions. Sustainability of cath lab services remains a significant challenge especially in relation to the high cost of sundries and other consumables amidst a limited budget. Conclusion: A practical example of how centers in LMIC can set up and sustain a public cardiac catheterization laboratory is presented. Government support, research, and training collaborations, if present, become invaluable leverage opportunities.

New investigators in the time of the COVID-19 pandemic.

JCB checks in with newly independent cell biologists and learns about their experience running a lab during the COVID-19 pandemic.

Moving a research lab during the COVID-19 pandemic.

The COVID-19 pandemic has created additional challenges for mid-career investigators seeking new academic opportunities. JCB asked scientists to share their experiences of uprooting their research careers and laboratories during the pandemic.

Toward Minimal-Sensing Locomotion Mode Recognition for a Powered Knee-Ankle Prosthesis.

OBJECTIVE: Locomotion mode recognition (LMR) enables seamless and natural transitions between low-level control systems in a powered prosthesis. We present a new optimization framework for LMR that eliminates irrelevant or redundant features and measurement signals while still maintaining performance. METHODS: We use multi-objective biogeography-based optimization to find a compromise solution between performance and the minimization of feature set size. Experimental data are collected from four transfemoral users walking with a powered knee-ankle prosthesis. We compare the performance of LMR systems trained with the optimal feature subsets and with the full feature set using a deep neural network classifier across six locomotion modes: standing, flat-ground walking, stair up/down, and ramp up/down. RESULTS: Statistical tests indicate that classifier performance using the optimal feature subsets is statistically equal to that using the full feature set. The LMR trained with an optimal subset results in the 1.98% steady-state and 4.09% transitional error rates, while only using approximately 41% and 53% of the available features and sensors, respectively. CONCLUSION: Results thus indicate the capability of the proposed framework to achieve simultaneously accurate and low-complex LMR systems for transfemoral individuals with powered prostheses. SIGNIFICANCE: This framework would potentially lead to less frequent clinical visits needed for sensor replacement and calibrations, which may save health care costs and the prosthesis user's time and energy.

An Extensive Set of Kinematic and Kinetic Data for Individuals with Intact Limbs and Transfemoral Prosthesis Users.

This paper introduces an extensive human motion data set for typical activities of daily living. These data are crucial for the design and control of prosthetic devices for transfemoral prosthesis users. This data set was collected from seven individuals, including five individuals with intact limbs and two transfemoral prosthesis users. These data include the following types of movements: (1) walking at three different speeds; (2) walking up and down a 5-degree ramp; (3) stepping up and down; (4) sitting down and standing up. We provide full-body marker trajectories and ground reaction forces (GRFs) as well as joint angles, joint velocities, joint torques, and joint powers. This data set is publicly available at the website referenced in this paper. Data from flexion and extension of the hip, knee, and ankle are presented in this paper. However, the data accompanying this paper (available on the internet) include 46 distinct measurements and can be useful for validating or generating mathematical models to simulate the gait of both transfemoral prosthesis users and individuals with intact legs.

Ex ante coherence shifts.

Cushman characterizes rationalization as the inverse of rational reasoning, but this distinction is psychologically questionable. Coherence-based reasoning highlights a subtler form of bidirectionality: By distorting task attributes to make one course of action appear superior to its rivals, a patina of rationality is bestowed on the choice. This mechanism drives choice and action, rather than just following in their wake.

Gradient-Based Multi-Objective Feature Selection for Gait Mode Recognition of Transfemoral Amputees.

One control challenge in prosthetic legs is seamless transition from one gait mode to another. User intent recognition (UIR) is a high-level controller that tells a low-level controller to switch to the identified activity mode, depending on the user's intent and environment. We propose a new framework to design an optimal UIR system with simultaneous maximum performance and minimum complexity for gait mode recognition. We use multi-objective optimization (MOO) to find an optimal feature subset that creates a trade-off between these two conflicting objectives. The main contribution of this paper is two-fold: (1) a new gradient-based multi-objective feature selection (GMOFS) method for optimal UIR design; and (2) the application of advanced evolutionary MOO methods for UIR. GMOFS is an embedded method that simultaneously performs feature selection and classification by incorporating an elastic net in multilayer perceptron neural network training. Experimental data are collected from six subjects, including three able-bodied subjects and three transfemoral amputees. We implement GMOFS and four variants of multi-objective biogeography-based optimization (MOBBO) for optimal feature subset selection, and we compare their performances using normalized hypervolume and relative coverage. GMOFS demonstrates competitive performance compared to the four MOBBO methods. We achieve a mean classification accuracy of 97.14 % ± 1.51 % and 98.45 % ± 1.22 % with the optimal selected subset for able-bodied and amputee subjects, respectively, while using only 23% of the available features. Results thus indicate the potential of advanced optimization methods to simultaneously achieve accurate, reliable, and compact UIR for locomotion mode detection of lower-limb amputees with prostheses.

OGT (O-GlcNAc Transferase) Selectively Modifies Multiple Residues Unique to Lamin A.

The LMNA gene encodes lamins A and C with key roles in nuclear structure, signaling, gene regulation, and genome integrity. Mutations in LMNA cause over 12 diseases ('laminopathies'). Lamins A and C are identical for their first 566 residues. However, they form separate filaments in vivo, with apparently distinct roles. We report that lamin A is ß-O-linked N-acetylglucosamine-(O-GlcNAc)-modified in human hepatoma (Huh7) cells and in mouse liver. In vitro assays with purified O-GlcNAc transferase (OGT) enzyme showed robust O-GlcNAcylation of recombinant mature lamin A tails (residues 385⁻646), with no detectable modification of lamin B1, lamin C, or 'progerin' (Δ50) tails. Using mass spectrometry, we identified 11 O-GlcNAc sites in a 'sweet spot' unique to lamin A, with up to seven sugars per peptide. Most sites were unpredicted by current algorithms. Double-mutant (S612A/T643A) lamin A tails were still robustly O-GlcNAc-modified at seven sites. By contrast, O-GlcNAcylation was undetectable on tails bearing deletion Δ50, which causes Hutchinson⁻Gilford progeria syndrome, and greatly reduced by deletion Δ35. We conclude that residues deleted in progeria are required for substrate recognition and/or modification by OGT in vitro. Interestingly, deletion Δ35, which does not remove the majority of identified O-GlcNAc sites, does remove potential OGT-association motifs (lamin A residues 622⁻625 and 639⁻645) homologous to that in mouse Tet1. These biochemical results are significant because they identify a novel molecular pathway that may profoundly influence lamin A function. The hypothesis that lamin A is selectively regulated by OGT warrants future testing in vivo, along with two predictions: genetic variants may contribute to disease by perturbing OGT-dependent regulation, and nutrient or other stresses might cause OGT to misregulate wildtype lamin A.

Optimal Mixed Tracking/Impedance Control With Application to Transfemoral Prostheses With Energy Regeneration.

OBJECTIVE: We design an optimal passivity-based tracking/impedance control system for a robotic manipulator with energy regenerative electronics, where the manipulator has both actively and semi-actively controlled joints. The semi-active joints are driven by a regenerative actuator that includes an energy-storing element. METHOD: External forces can have a large influence on energy regeneration characteristics. Impedance control is used to impose a desired relationship between external forces and deviation from reference trajectories. Multi-objective optimization (MOO) is used to obtain optimal impedance parameters and control gains to compromise between the two conflicting objectives of trajectory tracking and energy regeneration. We solve the MOO problem under two different scenarios: 1) constant impedance; and 2) time-varying impedance. RESULTS: The methods are applied to a transfemoral prosthesis simulation with a semi-active knee joint. Normalized hypervolume and relative coverage are used to compare Pareto fronts, and these two metrics show that time-varying impedance provides better performance than constant impedance. The solution with time-varying impedance with minimum tracking error (0.0008 rad) fails to regenerate energy (loses 9.53 J), while a solution with degradation in tracking (0.0452 rad) regenerates energy (gains 270.3 J). A tradeoff solution results in fair tracking (0.0178 rad) and fair energy regeneration (131.2 J). CONCLUSION: Our experimental results support the possibility of net energy regeneration at the semi-active knee joint with human-like tracking performance. SIGNIFICANCE: The results indicate that advanced control and optimization of ultracapacitor-based systems can significantly reduce power requirements in transfemoral prostheses.

Hybrid Nonlinear Disturbance Observer Design for Underactuated Bipedal Robots.

Existence of disturbances in unknown environments is a pervasive challenge in robotic locomotion control. Disturbance observers are a class of unknown input observers that have been extensively used for disturbance rejection in numerous robotics applications. In this paper, we extend a class of widely-used nonlinear disturbance observers to underactuated bipedal robots, which are controlled using hybrid zero dynamics-based control schemes. The proposed hybrid nonlinear disturbance observer provides the autonomous biped robot control system with disturbance rejection capabilities, while the underlying hybrid zero-dynamics based control law remains intact.

Significant radiation reduction in interventional fluoroscopy using a novel eye controlled movable region of interest.

PURPOSE: This paper reports the first results obtained using a novel technology called eye controlled region of interest (ECR) that substantially reduces both staff and patient irradiation during an interventional fluoroscopy procedure without interfering with workflow. Its collimator includes a partially x-ray attenuating plate with a nonattenuating aperture. An eye tracker follows the operator's gaze to automatically position the aperture to the clinical region of interest (CROI) anywhere in the image in real-time. METHODS: Experiments were performed in a swine model using a mobile fluoroscope with a 30 cm image intensifier and manual control of fluoroscopic factors. The factory collimator and image display monitor were replaced with different components for this study. The full 30 cm field-of-view (FOV) of the image intensifier was irradiated at normal levels, and served as a baseline, when ECR was disengaged. With ECR engaged, most of the 30 cm FOV was irradiated to less than 20% of normal levels while the CROI was normally irradiated. Animal irradiation was determined by physical KAP (kerma area product) measurements. Operator irradiation was characterized by air kerma and air kerma rate measurements near the operator. Data were collected from three pairs of interventions in each of five swine models. RESULTS: When ECR was engaged, KAP was reduced to 0.22 (p < 0.001) of baseline and operator irradiation to 0.27 (p < 0.001) of baseline. Overall procedure time had a borderline increase (p = 0.07) but fluoroscopy time was unchanged (p = 0.36) (Wilcoxon signed rank). Measured staff and patient radiation reductions are consistent with this collimator's design. Subjective impressions of imaging improvements are consistent with less scatter reaching the CROI. Engaging ECR reduced irradiation without subjectively or objectively increasing operator workload. CONCLUSIONS: The first in vivo evaluation of ECR demonstrated that this technology has objectively reduced KAP and operator irradiation by approximately 75% without interfering with the performance of fluoroscopically guided interventional procedures. In addition, reduced scatter production subjectively improved device visualization. These findings indicate the practicability of achieving better radiation optimization.

Effects of Mechanical Ventilation on Heart Geometry and Mitral Valve Leaflet Coaptation During Percutaneous Edge-to-Edge Mitral Valve Repair.

OBJECTIVES: This study sought to evaluate a ventilation maneuver to facilitate percutaneous edge-to-edge mitral valve repair (PMVR) and its effects on heart geometry. BACKGROUND: In patients with challenging anatomy, the application of PMVR is limited, potentially resulting in insufficient reduction of mitral regurgitation (MR) or clip detachment. Under general anesthesia, however, ventilation maneuvers can be used to facilitate PMVR. METHODS: A total of 50 consecutive patients undergoing PMVR were included. During mechanical ventilation, different levels of positive end-expiratory pressure (PEEP) were applied, and parameters of heart geometry were assessed using transesophageal echocardiography. RESULTS: We found that increased PEEP results in elevated central venous pressure. Specifically, central venous pressure increased from 14.0 ± 6.5 mm Hg (PEEP 3 mm Hg) to 19.3 ± 5.9 mm Hg (PEEP 20 mm Hg; p < 0.001). As a consequence, the reduced pre-load resulted in reduction of the left ventricular end-systolic diameter from 43.8 ± 10.7 mm (PEEP 3 mm Hg) to 39.9 ± 11.0 mm (PEEP 20 mm Hg; p < 0.001), mitral valve annulus anterior-posterior diameter from 32.4 ± 4.3 mm (PEEP 3 mm Hg) to 30.5 ± 4.4 mm (PEEP 20 mm Hg; p < 0.001), and the medio-lateral diameter from 35.4 ± 4.2 mm to 34.1 ± 3.9 mm (p = 0.002). In parallel, we observed a significant increase in leaflet coaptation length from 3.0 ± 0.8 mm (PEEP 3 mm Hg) to 5.4 ± 1.1 mm (PEEP 20 mm Hg; p < 0.001). The increase in coaptation length was more pronounced in MR with functional or mixed genesis. Importantly, a coaptation length >4.9 mm at PEEP of 10 mm Hg resulted in a significant reduction of PMVR procedure time (152 ± 49 min to 116 ± 26 min; p = 0.05). CONCLUSIONS: In this study, we describe a novel ventilation maneuver improving mitral valve coaptation length during the PMVR procedure, which facilitates clip positioning. Our observations could help to improve PMVR therapy and could make nonsurgical candidates accessible to PMVR therapy, particularly in challenging cases with functional MR.

The Elasticity of Preferences.

We explore how preferences for attributes are constructed when people choose between multiattribute options. As found in prior research, we observed that while people make decisions, their preferences for the attributes in question shift to support the emerging choice, thus enabling confident decisions. The novelty of the studies reported here is that participants repeated the same task 6 to 8 weeks later. We found that between tasks, preferences returned to near their original levels, only to shift again to support the second choice, regardless of which choice participants made. Similar patterns were observed in a free-choice task (Study 1) and when the favorableness of options was manipulated (Study 2). It follows that preferences behave in an elastic manner: In the absence of situational pressures, they rest at baseline levels, but during the process of reaching a decision, they morph to support the chosen options. This elasticity appears to facilitate confident decision making in the face of decisional conflict.

Statistical Mechanics Approximation of Biogeography-Based Optimization.

Biogeography-based optimization (BBO) is an evolutionary algorithm inspired by biogeography, which is the study of the migration of species between habitats. This paper derives a mathematical description of the dynamics of BBO based on ideas from statistical mechanics. Rather than trying to exactly predict the evolution of the population, statistical mechanics methods describe the evolution of statistical properties of the population fitness. This paper uses the one-max problem, which has only one optimum and whose fitness function is the number of 1s in a binary string, to derive equations that predict the statistical properties of BBO each generation in terms of those of the previous generation. These equations reveal the effect of migration and mutation on the population fitness dynamics of BBO. The results obtained in this paper are similar to those for the simple genetic algorithm with selection and mutation. The paper also derives equations for the population fitness dynamics of general separable functions, and we find that the results obtained for separable functions are the same as those for the one-max problem. The statistical mechanics theory of BBO is shown to be in good agreement with simulation.