Terahertz bandwidth photonic Hilbert transformers and implementations in ultra wideband single-sideband filters

Planar Bragg grating based photonic Hilbert transformers (PHTs) with THz bandwidths are proposed and practically demonstrated. An X-coupler, PHT, and a flat-top reflector are incorporated, demonstrating 2THz all-optical single-sideband filters. Devices are fabricated via a direct UV grating writing technique on a silica-on-silicon platform

Ultra-wide detuning planar Bragg grating fabrication technique based on direct UV grating writing with electro-optic phase modulation

A direct UV grating writing technique based on phase-controlled interferometry is proposed and demonstrated in a silica-on-silicon platform, with a wider wavelength detuning range than any previously reported UV writing technology. Electro-optic phase modulation of one beam in the interferometer is used to manipulate the fringe pattern and thus control the parameters of the Bragg gratings and waveguides. Various grating structures with refractive index apodization, phase shifts and index contrasts of up to 0.8×10-3 have been demonstrated. The method offers significant time/energy efficiency as well as simplified optical layout and fabrication process. We have shown Bragg gratings can be made from 1200 nm to 1900 nm exclusively under software control and the maximum peak grating reflectivity only decreases by 3dB over a 250 nm (~32THz) bandwidth

Simple planar Bragg grating devices for photonic Hilbert transform

Hilbert transformers are important devices widely used in information processing and signal analysis in the electronic domain. For example, for spectral efficiency improvement, it is used to construct the analytic signal for single sideband (SSB) modulation from a real signal. Photonic Hilbert transformers (PHTs) are proposed for a similar range of applications and would allow the direct processing of optical signals at bandwidths far beyond current electronic technologies

Post-communist capital city tourism representation: a case-study on Bucharest

The focus of the project is on the tourism representations of Central and Eastern European post-communist capital cities and the process of representation. Drawing from a number of academic fields such as urban tourism, culture, marketing, and media, as well as original primary and secondary research, the study wishes to contribute to existing debates on tourism representations and post-communist Central and Eastern European city tourism. Bucharest is the case-study. The project adopts a multi-method qualitative approach in line with the social-constructivist paradigm. Analysis of findings employs NVivo8 content analysis programme. Findings reflect on the thin line between representation producers and consumers and on the cyclical nature of the representation process. Bucharest representations are dominated by stereotypical images of the destination, both on the projected and perceived side. There is a strong overlap between the representations and images of Romania and of its capital. Disagreements exist between the projected tourism representations of tourism government, tourism industry, and tourism media, and how tourists and potential tourists perceive the city and its projected representations. The tourism representations projected by Bucharest representation-makers are determined by an ongoing process of self-rediscovery and reaffirmation of a European identity. Bucharest’s projected tourism representations are strongly affected by politics, transition and change. They are unstable and adapted to satisfy new political wills and urban regimes. On the other hand, tourists and potential tourists are attracted by the distinctiveness of the city, by its ‘Eastern’ characteristics, and by the change from communism to democracy. While tourist testimonials seem to be strongly influenced by tourism media destination representations, especially guidebooks, potential tourists perceive projected destination representations as unappealing and creating false expectations

Análise econômico-financeira da produção de carvão vegetal no Rio Grande do Sul.

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Schizophrenia Classification using Resting State EEG Functional Connectivity: Source Level Outperforms Sensor Level

Disrupted Functional and Structural Connectivity Measures Have Been Used to Distinguish Schizophrenia Patients from Healthy Controls. Classification Methods based on Functional Connectivity Derived from EEG Signals Are Limited by the Volume Conduction Problem. Recorded Time Series at Scalp Electrodes Capture a Mixture of Common Sources Signals, Resulting in Spurious Connections. We Have Transformed Sensor Level Resting State EEG Times Series to Source Level EEG Signals Utilizing a Source Reconstruction Method. Functional Connectivity Networks Were Calculated by Computing Phase Lag Values between Brain Regions at Both the Sensor and Source Level. Brain Complex Network Analysis Was Used to Extract Features and the Best Features Were Selected by a Feature Selection Method. a Logistic Regression Classifier Was Used to Distinguish Schizophrenia Patients from Healthy Controls at Five Different Frequency Bands. the Best Classifier Performance Was based on Connectivity Measures Derived from the Source Space and the Theta Band.The Transformation of Scalp EEG Signals to Source Signals Combined with Functional Connectivity Analysis May Provide Superior Features for Machine Learning Applications

Enhanced Neurologic Concept Recognition using a Named Entity Recognition Model based on Transformers

Although Deep Learning Has Been Applied to the Recognition of Diseases and Drugs in Electronic Health Records and the Biomedical Literature, Relatively Little Study Has Been Devoted to the Utility of Deep Learning for the Recognition of Signs and Symptoms. the Recognition of Signs and Symptoms is Critical to the Success of Deep Phenotyping and Precision Medicine. We Have Developed a Named Entity Recognition Model that Uses Deep Learning to Identify Text Spans Containing Neurological Signs and Symptoms and Then Maps These Text Spans to the Clinical Concepts of a Neuro-Ontology. We Compared a Model based on Convolutional Neural Networks to One based on Bidirectional Encoder Representation from Transformers. Models Were Evaluated for Accuracy of Text Span Identification on Three Text Corpora: Physician Notes from an Electronic Health Record, Case Histories from Neurologic Textbooks, and Clinical Synopses from an Online Database of Genetic Diseases. Both Models Performed Best on the Professionally-Written Clinical Synopses and Worst on the Physician-Written Clinical Notes. Both Models Performed Better When Signs and Symptoms Were Represented as Shorter Text Spans. Consistent with Prior Studies that Examined the Recognition of Diseases and Drugs, the Model based on Bidirectional Encoder Representations from Transformers Outperformed the Model based on Convolutional Neural Networks for Recognizing Signs and Symptoms. Recall for Signs and Symptoms Ranged from 59.5% to 82.0% and Precision Ranged from 61.7% to 80.4%. with Further Advances in NLP, Fully Automated Recognition of Signs and Symptoms in Electronic Health Records and the Medical Literature Should Be Feasible

Autonomous Control of a Line Follower Robot Using a Q-Learning Controller

In this paper, a MIMO simulated annealing (SA)-based Q-learning method is proposed to control a line follower robot. The conventional controller for these types of robots is the proportional (P) controller. Considering the unknown mechanical characteristics of the robot and uncertainties such as friction and slippery surfaces, system modeling and controller designing can be extremely challenging. The mathematical modeling for the robot is presented in this paper, and a simulator is designed based on this model. The basic Q-learning methods are based pure exploitation and the ε -greedy methods, which help exploration, can harm the controller performance after learning completion by exploring nonoptimal actions. The simulated annealing–based Q-learning method tackles this drawback by decreasing the exploration rate when the learning increases. The simulation and experimental results are provided to evaluate the effectiveness of the proposed controller