Optimizations for Wave-Controlled Metasurface-Based Reconfigurable Intelligent Surfaces

As the number of devices that require wireless access increases and the environment becomes more complex, Reconfigurable Intelligent Surfaces (RIS) -- structures that employ metasurfaces with tunable phase shifts -- provide the means to passively reflect incoming electromagnetic signals towards desired directions and away from others, where direct reception of the signal from the transmitter base station may not always be possible. This allows for a wider dynamic coverage of the environment while reducing the need to place more base station antennas for wireless communications. One difficulty with the implementation of RIS is its control -- to create the programmable phase shifts, each RIS element needs to have its own reflection coefficient determined by varying its impedance. This can be done by applying a specific voltage bias to a varactor diode connected to the element. Though, this becomes an issue when more RIS elements are added and controlled individually, as the wiring and configuration of the system become more complex. This research builds upon the idea of tuning the RIS elements using standing waves on transmission lines on the back of the RIS structure, and sampling the voltages using dedicated circuitry at each varactor diode location to create the controlled phase shifts. Different methods to sample the voltages by using envelope detectors or sample-and-hold circuits are explored. For each implementation, various analytical and nonlinear optimization algorithms are proposed to achieve desired radiation patterns both when steering power towards multiple intended receiver directions, and when forming nulls in other directions. The performances of these algorithms are analyzed through simulations, verifying their feasibility in practical RIS settings where convergence speed and accurate radiation patterns are critical. Finally, the scalability of wave-controlled RIS structures is analyzed with options to use machine learning algorithms to adapt the RIS to the environment and minimize the number of calculations required over time to generate desired beam patterns

DRIVE: One-bit Distributed Mean Estimation

We consider the problem where $n$ clients transmit $d$-dimensional real-valued vectors using $d(1+o(1))$ bits each, in a manner that allows the receiver to approximately reconstruct their mean. Such compression problems naturally arise in distributed and federated learning. We provide novel mathematical results and derive computationally efficient algorithms that are more accurate than previous compression techniques. We evaluate our methods on a collection of distributed and federated learning tasks, using a variety of datasets, and show a consistent improvement over the state of the art.Comment: Appears in NeurIPS 202

Communication-Efficient Federated Learning via Robust Distributed Mean Estimation

Distributed Mean Estimation (DME) is a central building block in federated learning, where clients send local gradients to a parameter server for averaging and updating the model. Due to communication constraints, clients often use lossy compression techniques to compress the gradients, resulting in estimation inaccuracies. DME is more challenging when clients have diverse network conditions, such as constrained communication budgets and packet losses. In such settings, DME techniques often incur a significant increase in the estimation error leading to degraded learning performance. In this work, we propose a robust DME technique named EDEN that naturally handles heterogeneous communication budgets and packet losses. We derive appealing theoretical guarantees for EDEN and evaluate it empirically. Our results demonstrate that EDEN consistently improves over state-of-the-art DME techniques

Phosphorylation of cytochrome b6 by the LHC II kinase associated with the cytochrome complex

AbstractThe cytochrome b6 polypeptide present in cytochrome b6/| preparations from spinach thylakoids is phosphorylated concomitantly with the autophosphorylation of the 64 kDa polypeptide identified as the redox-controlled LHCII kinase. The N-terminal sequence of the 64 kDa kinase and sequence analysis of cytochrome b6 indicate the existence of putative phosphorylation sites in both proteins

Depth electrode neurofeedback with a virtual reality interface

Invasive brain–computer interfaces (BCI) provide better signal quality in terms of spatial localization, frequencies and signal/noise ratio, in addition to giving access to deep brain regions that play important roles in cognitive or affective processes. Despite some anecdotal attempts, little work has explored the possibility of integrating such BCI input into more sophisticated interactive systems like those which can be developed with game engines. In this article, we integrated an amygdala depth electrode recorder with a virtual environment controlling a virtual crowd. Subjects were asked to down regulate their amygdala using the level of unrest in the virtual room as feedback on how successful they were. We report early results which suggest that users adapt very easily to this paradigm and that the timing and fluctuations of amygdala activity during self-regulation can be matched by crowd animation in the virtual room. This suggests that depth electrodes could also serve as high-performance affective interfaces, notwithstanding their strictly limited availability, justified on medical grounds only

Kronecker-Product Beamforming With Sparse Concentric Circular Arrays

This article presents a Kronecker-product (KP) beamforming approach incorporating sparse concentric circular arrays (SCCAs). The locations of the microphones on the SCCA are optimized concerning the broadband array directivity over a wide range of direction-of-arrival (DOA) deviations of a desired signal. A maximum directivity factor (MDF) sub-beamformer is derived accordingly with the optimal locations. Then, we propose two global beamformers obtained as a Kronecker product of a uniform linear array (ULA) and the SCCA sub-beamformer. The global beamformers differ by the type of the ULA, which is designed either as an MDF sub-beamformer along the $\mathsf {x}$-axis or as a maximum white noise gain sub-beamformer along the $\mathsf {y}$-axis. We analyze the performance of the proposed beamformers in terms of the directivity factor, the white noise gain, and their spatial beampatterns. Compared to traditional beamformers, the proposed beamformers exhibit considerably larger tolerance to DOA deviations concerning both the azimuth and elevation angles. Experimental results with speech signals in noisy and reverberant environments demonstrate that the proposed approach outperforms traditional beamformers regarding the perceptual evaluation of speech quality (PESQ) and short-time objective intelligibility (STOI) scores when the desired speech signals deviate from the nominal DOA

Double disparities in the health care for people with schizophrenia of an ethnic-national minority

Abstract Background Studies have shown health care disparities among persons of minority status, including in countries with universal health care. Yet, a dearth of studies have addressed disparities resulting from the combined effect of two minority status groups: severe mental illness and ethnic-national sector filiation. This study aimed to compare the differential health care of Jewish- and Arab-Israelis with schizophrenia in a country with a universal health insurance. Method This study builds on a large case-control epidemiological sample (N = 50,499) of Jewish- (92.9%) and Arab-Israelis (7.1%) service users with (n = 16,833) and without schizophrenia (n = 33,666). Health services records were collected in the years 2000–2009. Diabetes and cardiovascular disease (CVD) served as sentinel diseases. We compared annual number of LDL tests and visits to specialists in the entire sample, Hemoglobin-A1C test among people diagnosed with diabetes, and cardiac surgical interventions for those diagnosed with CVD. Results Service users with schizophrenia were less likely to meet identical indexes of care as their study counterparts: 95% of cholesterol tests (p < .001), and 92% visits to specialists (p < .001). These differences were greater among Arab- compared to Jewish-Israelis. Annual frequency of Hemoglobin-A1C test among people diagnosed with diabetes was lower (94%) in people with schizophrenia (p < 0.01), but no ethnic-national differences were identified. Among service users with CVD less surgical interventions were done in people with schizophrenia (70%) compared to their counterparts, with no ethnic-national disparities. Conclusions In Israel, service users with schizophrenia fail to receive equitable levels of medical and cardiac surgical care for CVD and regular laboratory tests for diabetes. Although disparities in some health indicators were enhanced among Arab-Israelis, schizophrenia was a greater source of disparities than ethnic-national filiation