Optical coherence tomography-based consensus definition for lamellar macular hole.

BackgroundA consensus on an optical coherence tomography definition of lamellar macular hole (LMH) and similar conditions is needed.MethodsThe panel reviewed relevant peer-reviewed literature to reach an accord on LMH definition and to differentiate LMH from other similar conditions.ResultsThe panel reached a consensus on the definition of three clinical entities: LMH, epiretinal membrane (ERM) foveoschisis and macular pseudohole (MPH). LMH definition is based on three mandatory criteria and three optional anatomical features. The three mandatory criteria are the presence of irregular foveal contour, the presence of a foveal cavity with undermined edges and the apparent loss of foveal tissue. Optional anatomical features include the presence of epiretinal proliferation, the presence of a central foveal bump and the disruption of the ellipsoid zone. ERM foveoschisis definition is based on two mandatory criteria: the presence of ERM and the presence of schisis at the level of Henle's fibre layer. Three optional anatomical features can also be present: the presence of microcystoid spaces in the inner nuclear layer (INL), an increase of retinal thickness and the presence of retinal wrinkling. MPH definition is based on three mandatory criteria and two optional anatomical features. Mandatory criteria include the presence of a foveal sparing ERM, the presence of a steepened foveal profile and an increased central retinal thickness. Optional anatomical features are the presence of microcystoid spaces in the INL and a normal retinal thickness.ConclusionsThe use of the proposed definitions may provide uniform language for clinicians and future research

Feedback Effects on Mind Wandering: A Series of Online Experiments

Replicating in-lab experiments online can ensure scientific progress when physical contact is discouraged, like during the covid-19 pandemic. In this thesis, we replicated the results from Boayue et al. (2021) in-lab Mind Wandering (MW) experiment online. The task uses the Finger-Tapping Random Sequence Generation Task, a sustained attention task, equating MW with Task Unrelated Thoughts (TUTs). In addition to collecting self-reported TUTs, the FT-RSGT continuously collects Behavioural Variability (BV) and Approximate Entropy (AE), which are both related to MW. We replicated Boayue et al. (2021) in-lab results showing that we can reliably conduct MW experiments online. Moreover, by using six different versions of the task, we investigated whether giving different types of feedback to the participants could improve their task focus. The task versions were: (1) Identical to the lab-based task. (2) Performance feedback training. (3) Intermittently delivered performance feedback throughout the experiment. (4) Non-specific feedback. (5) Camera monitoring feedback and (6) progression feedback. We consistently found that specific performance feedback increased the global on-task focus as measured by our behavioural indices (AE and BV) relative to non-specific motivational feedback, leaving self-reported MW unaffected. On the other hand, progression and camera feedback increased the magnitude of the subjectively reported MW while leaving task performance unchanged. This dissociation could result from participants' exaggeration when surveilled and their novelty with the self-rating. We conclude that, during online experiments, researchers may want to incorporate performance feedback to increase behavioural indices. These insights may apply to other situations where increased task performance is desired. All data, experimental materials, and pre-registrations are available at the Open Science Framework (https://osf.io/wjvk2)

Multivariable Sliding Mode Control Design for Aircraft Engines

Many control theories are used in controlling aircraft engines. However, the multivariablesliding mode control is not yet established in this application even though ithas a lot of potential in dealing with complex and nonlinear systems such as aircraftengines. Therefore, a guideline in developing multivariable sliding mode control law for an aircraft engine is presented in this thesis. The problem of chattering in thesliding mode control is suppressed by the use of the boundary layer method. The controllogic is tested by implementing NASA\u27s Commercial Modular Aero-PropulsionSystem Simulation 40k (C-MAPSS40k). Simulation results are analyzed and comparedto the results obtained from the baseline controller. The robust property of multivariable sliding mode control is also examined by altering the flight condition ofthe engin

Multivariable Sliding Mode Control Design for Aircraft Engines

Many control theories are used in controlling aircraft engines. However, the multivariablesliding mode control is not yet established in this application even though ithas a lot of potential in dealing with complex and nonlinear systems such as aircraftengines. Therefore, a guideline in developing multivariable sliding mode control law for an aircraft engine is presented in this thesis. The problem of chattering in thesliding mode control is suppressed by the use of the boundary layer method. The controllogic is tested by implementing NASA\u27s Commercial Modular Aero-PropulsionSystem Simulation 40k (C-MAPSS40k). Simulation results are analyzed and comparedto the results obtained from the baseline controller. The robust property of multivariable sliding mode control is also examined by altering the flight condition ofthe engin

Optimal Switching for Hybrid Semilinear Evolutions

We consider the optimization of a dynamical system by switching at discrete time points between abstract evolution equations composed by nonlinearly perturbed strongly continuous semigroups, nonlinear state reset maps at mode transition times and Lagrange-type cost functions including switching costs. In particular, for a fixed sequence of modes, we derive necessary optimality conditions using an adjoint equation based representation for the gradient of the costs with respect to the switching times. For optimization with respect to the mode sequence, we discuss a mode-insertion gradient. The theory unifies and generalizes similar approaches for evolutions governed by ordinary and delay differential equations. More importantly, it also applies to systems governed by semilinear partial differential equations including switching the principle part. Examples from each of these system classes are discussed

Robust Bang-Off-Bang Low-Thrust Guidance Using Model Predictive Static Programming

Model Predictive Static Programming (MPSP) was always used under the assumption of continuous control, which impedes it for applications with bang-off-bang control directly. In this paper, MPSP is employed for the first time as a guidance scheme for low-thrust transfers with bang-off-bang control where the fuel-optimal trajectory is used as the nominal solution. In our method, dynamical equations in Cartesian coordinates are augmented by the mass costate equation, while the unconstrained velocity costate vector is used as control variable, and is expressed as a combination of Fourier basis functions with corresponding weights. A two-loop MPSP algorithm is designed where the weights and the initial mass costate are updated in the inner loop and continuation is conducted on the outer loop in case of large perturbations. The sensitivity matrix (SM) is recursively calculated using analytical derivatives and SM at switching points is compensated based on calculus of variations. An sample interplanetary CubeSat mission to an asteroid is used as study case to illustrate the effectiveness of the method developed

Distributed filtering of networked dynamic systems with non-gaussian noises over sensor networks: A survey

summary:Sensor networks are regarded as a promising technology in the field of information perception and processing owing to the ease of deployment, cost-effectiveness, flexibility, as well as reliability. The information exchange among sensors inevitably suffers from various network-induced phenomena caused by the limited resource utilization and complex application scenarios, and thus is required to be governed by suitable resource-saving communication mechanisms. It is also noteworthy that noises in system dynamics and sensor measurements are ubiquitous and in general unknown but can be bounded, rather than follow specific Gaussian distributions as assumed in Kalman-type filtering. Particular attention of this paper is paid to a survey of recent advances in distributed filtering of networked dynamic systems with non-Gaussian noises over sensor networks. First, two types of widely employed structures of distributed filters are reviewed, the corresponding analysis is systematically addressed, and some interesting results are provided. The inherent purpose of adding consensus terms into the distributed filters is profoundly disclosed. Then, some representative models characterizing various network-induced phenomena are reviewed and their corresponding analytical strategies are exhibited in detail. Furthermore, recent results on distributed filtering with non-Gaussian noises are sorted out in accordance with different network-induced phenomena and system models. Another emphasis is laid on recent developments of distributed filtering with various communication scheduling, which are summarized based on the inherent characteristics of their dynamic behavior associated with mathematical models. Finally, the state-of-the-art of distributed filtering and challenging issues, ranging from scalability, security to applications, are raised to guide possible future research