Estimation and control with limited information and unreliable feedback

Advancement in sensing technology is introducing new sensors that can provide information that was not available before. This creates many opportunities for the development of new control systems. However, the measurements provided by these sensors may not follow the classical assumptions from the control literature. As a result, standard control tools fail to maximize the performance in control systems utilizing these new sensors. In this work we formulate new assumptions on the measurements applicable to new sensing capabilities, and develop and analyze control tools that perform better than the standard tools under these assumptions. Specifically, we make the assumption that the measurements are quantized. This assumption is applicable, for example, to low resolution sensors, remote sensing using limited bandwidth communication links, and vision-based control. We also make the assumption that some of the measurements may be faulty. This assumption is applicable to advanced sensors such as GPS and video surveillance, as well as to remote sensing using unreliable communication links. The first tool that we develop is a dynamic quantization scheme that makes a control system stable to any bounded disturbance using the minimum number of quantization regions. Both full state feedback and output feedback are considered, as well as nonlinear systems. We further show that our approach remains stable under modeling errors and delays. The main analysis tool we use for proving these results is the nonlinear input-to-state stability property. The second tool that we analyze is the Minimum Sum of Distances estimator that is robust to faulty measurements. We prove that this robustness is maintained when the measurements are also corrupted by noise, and that the estimate is stable with respect to such noise. We also develop an algorithm to compute the maximum number of faulty measurements that this estimator is robust to. The last tool we consider is motivated by vision-based control systems. We use a nonlinear optimization that is taking place over both the model parameters and the state of the plant in order to estimate these quantities. Using the example of an automatic landing controller, we demonstrate the improvement in performance attainable with such a tool

Volitional limbic neuromodulation has a multifaceted clinical benefit in Fibromyalgia patients

Volitional neural modulation using neurofeedback has been indicated as a potential treatment for chronic conditions that involve peripheral and central neural dysregulation. Here we utilized neurofeedback in patients suffering from Fibromyalgia - a chronic pain syndrome that involves sleep disturbance and emotion dysregulation. These ancillary symptoms, which have an amplification effect on pain, are known to be mediated by heightened limbic activity. In order to reliably probe limbic activity in a scalable manner fit for EEG-neurofeedback training, we utilized an Electrical Finger Print (EFP) model of amygdala-BOLD signal (termed Amyg-EFP), that has been successfully validated in our lab in the context of volitional neuromodulation. We anticipated that Amyg-EFP-neurofeedback training aimed at limbic down modulation should improve chronic pain in patients suffering from Fibromyalgia, by balancing disturbed indices for sleep and affect. We further expected that improved clinical status would correspond to successful training as indicated by improved down modulation of the Amygdala-EFP signal. Thirty-Four Fibromyalgia patients (31F; age 35.6 ± 11.82) participated in a randomized placebo-controlled trial with biweekly Amyg-EFP-neurofeedback sessions and placebo of sham neurofeedback (n = 9) for a total duration of five consecutive weeks. Following training, participants in the Real-neurofeedback group were divided into good (n = 13) or poor (n = 12) modulators according to their success in the neurofeedback training. Before and after treatment, self-reports on pain, depression, anxiety, fatigue and sleep quality were obtained, as well as objective sleep Indices. Long-term clinical follow-up was made available, within up to three years of the neurofeedback training completion. REM latency and objective sleep quality index were robustly improved following the treatment course only in the Real-neurofeedback group (both time × group p < 0.05) and to a greater extent among good modulators (both time*sub-group p < 0.05). In contrast, self-report measures did not reveal a treatment-specific response at the end of the treatment. However, the follow-up assessment revealed a delayed improvement in chronic pain and subjective sleep experience, evident only in the Real-neurofeedback group (both time × group p < 0.05). Moderation analysis showed that the enduring clinical effects on pain evident in the follow-up assessment were predicted by the immediate improvements following training in objective sleep and subjective affect measures. Our findings suggest that Amyg-EFP- neurofeedback that specifically targets limbic activity down modulation offers a successful principled approach for volitional EEG based neuromodulation training in Fibromyalgia patients. Importantly, it seems that via its immediate sleep improving effect, the neurofeedback training induced a delayed reduction in the target subjective symptom of chronic pain, far and beyond the immediate placebo effect. This indirect approach to chronic pain management reflects the necessary link between somatic and affective dysregulation that can be successfully targeted using neurofeedback

Privatisation, outsourcing and employment relations in Israel

This chapter focuses on the effect that outsourcing, as a subset of privatization, has had on employment relations in Israel. In particular, chapter highlights the adverse, and perhaps counter-intuitive, effects that the law has had on the plight of Israeli contract workers. Israeli governmental agencies and local councils have turned to outsourcing as a means to circumventing post limits and due to the Ministry of Finance’s pressures to increase ‘flexibility’ in the civil service. Intriguingly, paradoxically, and tragically, the law’s effort to regulate this growing phenomenon has led employers resorting to tactics which have redefined agency workers (teachers, nurses, etc) as workers subject to the “outsourcing of services” (teaching, nursing, etc). This has moved such workers into a legal void, depriving them of rights and protection

Impact of COVID-19 on cardiovascular testing in the United States versus the rest of the world

Objectives: This study sought to quantify and compare the decline in volumes of cardiovascular procedures between the United States and non-US institutions during the early phase of the coronavirus disease-2019 (COVID-19) pandemic. Background: The COVID-19 pandemic has disrupted the care of many non-COVID-19 illnesses. Reductions in diagnostic cardiovascular testing around the world have led to concerns over the implications of reduced testing for cardiovascular disease (CVD) morbidity and mortality. Methods: Data were submitted to the INCAPS-COVID (International Atomic Energy Agency Non-Invasive Cardiology Protocols Study of COVID-19), a multinational registry comprising 909 institutions in 108 countries (including 155 facilities in 40 U.S. states), assessing the impact of the COVID-19 pandemic on volumes of diagnostic cardiovascular procedures. Data were obtained for April 2020 and compared with volumes of baseline procedures from March 2019. We compared laboratory characteristics, practices, and procedure volumes between U.S. and non-U.S. facilities and between U.S. geographic regions and identified factors associated with volume reduction in the United States. Results: Reductions in the volumes of procedures in the United States were similar to those in non-U.S. facilities (68% vs. 63%, respectively; p = 0.237), although U.S. facilities reported greater reductions in invasive coronary angiography (69% vs. 53%, respectively; p < 0.001). Significantly more U.S. facilities reported increased use of telehealth and patient screening measures than non-U.S. facilities, such as temperature checks, symptom screenings, and COVID-19 testing. Reductions in volumes of procedures differed between U.S. regions, with larger declines observed in the Northeast (76%) and Midwest (74%) than in the South (62%) and West (44%). Prevalence of COVID-19, staff redeployments, outpatient centers, and urban centers were associated with greater reductions in volume in U.S. facilities in a multivariable analysis. Conclusions: We observed marked reductions in U.S. cardiovascular testing in the early phase of the pandemic and significant variability between U.S. regions. The association between reductions of volumes and COVID-19 prevalence in the United States highlighted the need for proactive efforts to maintain access to cardiovascular testing in areas most affected by outbreaks of COVID-19 infection

Third-Order Nilpotency, Nice Reachability and Asymptotic Stability

We consider an affine control system whose vector fields span a third-order nilpotent Lie algebra. We show that the reachable set at time T using measurable controls is equivalent to the reachable set at time T using piecewise-constant controls with no more than four switches. The bound on the number of switches is uniform over any final time T. As a corollary, we derive a new su#cient condition for stability of nonlinear switched systems under arbitrary switching. This provides a partial solution to an open problem posed in [1]

Input-to-state stabilization with minimum number of quantization regions

We study control systems where the state measurements are quantized and time-sampled, and an unknown disturbance is being applied. We present a dynamic quantization scheme that switches between three modes of operation. We show that by using this scheme with a continuous static feedback controller we achieve a closed-loop system which has the Input-to-State Stability property (ISS). Our design does not use any characterization of the disturbance; as long as the disturbance is bounded the system will remain stable. We show that three quantization regions per dimension is sufficient to achieve the ISS property, and furthermore we show that the ISS property is achievable using a data rate that is arbitrarily close to the minimum required data rate when no disturbance is applied

Input-to-State Stabilization with Quantized Output Feedback ⋆

Abstract. We study control systems where the output subspace is covered by a finite set of quantization regions, and the only information available to a controller is which of the quantization regions currently contains the system’s output. We assume the dimension of the output subspace is strictly less than the dimension of the state space. The number of quantization regions can be as small as 3 per dimension of the output subspace. We show how to design a controller that stabilizes such a system, and makes the system robust to an external unknown disturbance in the sense that the closed-loop system has the Input-to-State Stability property. No information about the disturbance is required to design the controller. Achieving the ISS property for continuoustime systems with quantized measurements requires a hybrid approach, and indeed our controller consists of a dynamic, discrete-time observer, a continuous-time state-feedback stabilizer, and a switching logic that switches between several modes of operation. Except for some properties that the observer and the stabilizer must possess, our approach is general and not restricted to a specific observer or stabilizer. Examples of specific observers that possess these properties are included.

Computation and Relaxation of Conditions for Equivalence between l1 and l0 Minimization

National Science Foundation / NSF CAREER IIS-0347456, NSF CRS-EHS-0509151, NSF CCF-TF-051495ONR / ONR YIP N00014-05-1-063Ope

Clustering of Raft-Associated Proteins in the External Membrane Leaflet Modulates Internal Leaflet H-Ras Diffusion and Signaling

One of the least-explored aspects of cholesterol-enriched domains (rafts) in cells is the coupling between such domains in the external and internal monolayers and its potential to modulate transbilayer signal transduction. Here, we employed fluorescence recovery after photobleaching to study the effects of antibody-mediated patching of influenza hemagglutinin (HA) proteins [raft-resident wild-type HA and glycosylphosphatidylinositol-anchored HA, or the nonraft mutant HA(2A520)] on the lateral diffusion of internal-leaflet raft and nonraft Ras isoforms (H-Ras and K-Ras, respectively). Our studies demonstrate that the clustering of outer-leaflet or transmembrane raft-associated HA proteins (but not their nonraft mutants) retards the lateral diffusion of H-Ras (but not K-Ras), suggesting stabilized interactions of H-Ras with the clusters of raft-associated HA proteins. These modulations were paralleled by specific effects on the activity of H-Ras but not of the nonraft K-Ras. Thus, clustering raft-associated HA proteins facilitated the early step whereby H-Ras is converted to an activated, GTP-loaded state but inhibited the ensuing step of downstream signaling via the Mek/Erk pathway. We propose a model for the modulation of transbilayer signaling by clustering of raft proteins, where external clustering (antibody or ligand mediated) enhances the association of internal-leaflet proteins with the stabilized clusters, promoting either enhancement or inhibition of signaling