Experimental validation of XPM mitigation using a generalizable multi-task learning neural network.

We address the development of efficient neural network (NN)-based post-equalizers in long-haul coherent-detection dense wavelength-division multiplexing (DWDM) optical transmission systems. To achieve a high level of generalization of the NN-based equalizers, we propose to employ multi-task learning (MTL). MTL refers to a single shared machine learning (NN) model that can perform multiple different (albeit related) tasks.

Quick action required: revealing pheochromocytoma as the hidden trigger behind postoperative hypertensive crisis.

Managing patients who present with elevated blood pressure (BP) requires careful but expeditious assessment and triage to differentiate between those at immediate risk of complications and those for whom BP elevation does not pose an immediate threat to health. We present a case of a 54-year-old healthy male patient who experienced refractory hypertension during the immediate postoperative period following nasal surgery. Additional gastrointestinal symptoms and imaging findings made it possible to consider a catecholamine-producing tumour as the primary cause.

Attention-aided partial bidirectional RNN-based nonlinear equalizer in coherent optical systems.

We leverage the attention mechanism to investigate and comprehend the contribution of each input symbol of the input sequence and their hidden representations for predicting the received symbol in the bidirectional recurrent neural network (BRNN)-based nonlinear equalizer. In this paper, we propose an attention-aided novel design of a partial BRNN-based nonlinear equalizer, and evaluate with both LSTM and GRU units in a single-channel DP-64QAM 30Gbaud coherent optical communication systems of 20 × 50 km standard single-mode fiber (SSMF) spans. Our approach maintains the Q-factor performance of the baseline equalizer with a significant complexity reduction of ∼56.

Experimental implementation of a neural network optical channel equalizer in restricted hardware using pruning and quantization.

The deployment of artificial neural networks-based optical channel equalizers on edge-computing devices is critically important for the next generation of optical communication systems. However, this is still a highly challenging problem, mainly due to the computational complexity of the artificial neural networks (NNs) required for the efficient equalization of nonlinear optical channels with large dispersion-induced memory. To implement the NN-based optical channel equalizer in hardware, a substantial complexity reduction is needed, while we have to keep an acceptable performance level of the simplified NN model.

Neural networks for computing and denoising the continuous nonlinear Fourier spectrum in focusing nonlinear Schrödinger equation.

We combine the nonlinear Fourier transform (NFT) signal processing with machine learning methods for solving the direct spectral problem associated with the nonlinear Schrödinger equation. The latter is one of the core nonlinear science models emerging in a range of applications. Our focus is on the unexplored problem of computing the continuous nonlinear Fourier spectrum associated with decaying profiles, using a specially-structured deep neural network which we coined NFT-Net.

COVID-19-Associated Invasive Pulmonary Aspergillosis in the Intensive Care Unit: A Case Series in a Portuguese Hospital.

Invasive pulmonary aspergillosis (IPA) has become a recognizable complication in coronavirus disease 2019 (COVID-19) patients admitted to intensive care units (ICUs). Alveolar damage in the context of acute respiratory distress syndrome (ARDS) appears to be the culprit in facilitating fungal invasion in COVID-19 patients, leading to a COVID-19-associated pulmonary aspergillosis (CAPA) phenomenon. From November 2020 to 15 February 2021, 248 COVID-19 patients were admitted to our ICUs, of whom ten patients (4% incidence) were classified as either probable (six) or possible (four) CAPA cases.

Severe Aplastic Anemia Developed after Thymectomy: A Case Report and Literature Review.

Thymus neoplasms are frequently related to paraneoplastic autoimmune manifestations. Its most common associations are myasthenia gravis and pure red cell aplasia. Aplastic anemia has been increasingly documented as an initial presentation of thymoma.

Chemical monitoring of river water bodies in an EU outermost region: examples from the Azores archipelago (Portugal).

Chemical monitoring of water quality on a total of 16 rivers in the Azores archipelago (Portugal), since 2003, made it possible to identify the major pressures and spatial geochemical variations along main course of the rivers. River water pollution is to a large extent associated to point sources, namely domestic wastewater discharges, especially in urban areas, and diffuse sources, associated with pasture land, and explain the high values on BOD(5) and nutrients (P and N). Heavy metals and metalloids, as well as hydrocarbons and pesticides, are generally under the detection limits of the analytical methods.