Miracle-dz/UniFAR-FTUs huggingface dataset:
A Retrospective Study of Postictal Suppression during Electroconvulsive Therapy

Background: electroconvulsive therapy (ECT) is the most effective treatment in treatment-resistant depression (TRD), but its response remains partial. Identifying useful indicators to guide decision making for treatment and improve clinical response remains a major issue. The objective of the present retrospective study was to determine if clinical response—early (after 5 ECT sessions) or longer-term (after 12 ECT sessions)—was associated with postictal suppression during the first ECT course and/or with postictal suppression frequency during the whole ECT course. Methods: in a retrospective study, the data of 42 patients suffering from treatment-resistant depression and receiving at least 5 ECT sessions were collected. Two sessions per week of bitemporal brief-pulse ECT sessions were administered to patients. Each of the electroencephalography (EEG) recordings were assessed to determine the presence of postictal suppression. Results: the postictal suppression from the first ECT session predicted a better long-term clinical response (after 12 ECT sessions), but not early clinical response (after only 5 ECT sessions). The postictal suppression frequency was associated with neither the short- nor the long-term clinical response. In addition, postictal suppression and short-term cognitive performances were not associated. Conclusions: this EEG indicator is clinically useful if it appears in the first ECT sessions, but it is no longer relevant in the following sessions.
Operational safety performance indicators for nuclear power plants

A set of operational safety performance indicators for nuclear power plants(NPP) was developed to evaluate operational safety performance of NPP.The indicator system was based on the definition of NPP operational safety and includes eight primary specifications.The performance for each specification was monitored through performance indicators.Histogram analyses of the operational performance data were used to evaluate the performance information by describing the operational performance characteristics for plant operators and managers to analyze NPP operational safety.As a result,the indicator system can be used to oversee NPP operational performance to help improve the management of NPP operation safety.
Neutrino decay processes and flavour oscillations

We further develop the theory of the neutrino flavour oscillations accounting for the quantum decoherence effect engendered by the neutrino radiative decay in an external electromagnetic field. In particular, we have considered the most general form of the neutrino electromagnetic vertex and obtained in the explicit form the dissipative term in the neutrino master equation. It shown that the dissipative term depends on the neutrino radiative decay rates.
Molecular Interactions Associated with Coagulation of Organic Pollutants by 2S Albumin of Plant Proteins: A Computational Approach

The removal of organic pollutants is a major challenge in wastewater treatment technologies. Coagulation by plant proteins is a promising technique for this purpose. The use of these proteins has been experimentally investigated and reported in the literature. However, the determination of the molecular interactions of these species is experimentally challenging and the computational approach offers a suitable alternative in gathering useful information for this system. The present study used a molecular dynamic simulation approach to predict the potentials of using Moringa oleifera (MO), Arachis hypogaea, Bertholletia excelsa, Brassica napus, and Helianthus annuus plant proteins for the coagulation of organic pollutants and the possible mechanisms of coagulation of these proteins. The results showed that the physicochemical and structural properties of the proteins are linked to their performance. Maximum coagulation of organic molecules to the proteins is between 50–100%. Among five proteins studied for coagulation, Brassica napus and Helianthus annuus performed better than the well-known MO protein. The amino acid residues interacting with the organic molecules play a significant role in the coagulation and this is peculiar with each plant protein. Hydrogen bond and π—interactions dominate throughout the protein–pollutants molecular interactions. The reusability of the proteins after coagulation derived from their structural quality analysis along with the complexes looks promising and most of them are better than that of the MO. The results showed that the seed proteins studied have good prediction potentials to be used for the coagulation of organic pollutants from the environment, as well as the insights into their molecular activities for bioremediation.
Facial Expression Recognition to Aid Visually Impaired People

Facial expression recognition systems can help a visually impaired person to identify the emotions of the person with whom she interacts, assisting in her non-verbal communication. Among the various researches carried out in recent years on recognition of facial expressions, the best results obtained come from methods that use deep learning, mainly with the use of convolutional neural networks. This work presents a literature review on the problem of recognition of facial expressions, through the use of convolutional neural networks and proposes two approaches in which the first one uses pre-trained CNN models together with the Linear SVM classifier that, applied to the bases CK+ and JAFFE data, obtained maximum accuracy of 89.6% and 95.7%, respectively. And in the second approach, a CNN model built from scratch is used with the CK+ and FER2013 databases, which obtained accuracy rates of 85% and 65.8%, respectively.
The Effectiveness and Cost of an Intervention to Increase the Provision of Preventive Care in Community Mental Health Services: Protocol for a Cluster-Randomized Controlled Trial

Preventive care to address chronic disease risk behaviours is infrequently provided by community mental health services. In this cluster-randomised controlled trial, 12 community mental health services in 3 Local Health Districts in New South Wales, Australia, will be randomised to either an intervention group (implementing a new model of providing preventive care) or a control group (usual care). The model of care comprises three components: (1) a dedicated ‘healthy choices’ consultation offered by a ‘healthy choices’ clinician; (2) embedding information regarding risk factors into clients’ care plans; and (3) the continuation of preventive care by mental health clinicians in ongoing consultations. Evidence-based implementation strategies will support the model implementation, which will be tailored by being co-developed with service managers and clinicians. The primary outcomes are client-reported receipt of: (1) an assessment of chronic disease risks (tobacco smoking, inadequate fruit and vegetable consumption, harmful alcohol use and physical inactivity); (2) brief advice regarding relevant risk behaviours; and (3) referral to at least one behaviour change support. Resources to develop and implement the intervention will be captured to enable an assessment of cost effectiveness and affordability. The findings will inform the development of future service delivery initiatives to achieve guideline- and policy-concordant preventive care delivery.
In-air Hand Gesture Signature Recognition: An iHGS Database Acquisition Protocol

Background: With the advances in current technology, hand gesture recognition has gained considerable attention. It has been extended to recognize more distinctive movements, such as a signature, in human-computer interaction (HCI) which enables the computer to identify a person in a non-contact acquisition environment. This application is known as in-air hand gesture signature recognition. To our knowledge, there are no publicly accessible databases and no detailed descriptions of the acquisitional protocol in this domain. Methods: This paper aims to demonstrate the procedure for collecting the in-air hand gesture signature’s database. This database is disseminated as a reference database in the relevant field for evaluation purposes. The database is constructed from the signatures of 100 volunteer participants, who contributed their signatures in two different sessions. Each session provided 10 genuine samples enrolled using a Microsoft Kinect sensor camera to generate a genuine dataset. In addition, a forgery dataset was also collected by imitating the genuine samples. For evaluation, each sample was preprocessed with hand localization and predictive hand segmentation algorithms to extract the hand region. Then, several vector-based features were extracted. Results: In this work, classification performance analysis and system robustness analysis were carried out. In the classification analysis, a multiclass Support Vector Machine (SVM) was employed to classify the samples and 97.43% accuracy was achieved; while the system robustness analysis demonstrated low error rates of 2.41% and 5.07% in random forgery and skilled forgery attacks, respectively. Conclusions: These findings indicate that hand gesture signature is not only feasible for human classification, but its properties are also robust against forgery attacks.
Cellulosic Ethanol Production Using a Dual Functional Novel Yeast

Reducing the cost of cellulosic ethanol production, especially for cellulose hydrolytic enzymes, is vital to growing a sustainable and efficient cellulosic ethanol industry and bio-based economy. Using an ethanologenic yeast able to produce hydrolytic enzymes, such as Clavispora NRRL Y-50464, is one solution. NRRL Y-50464 is fast-growing and robust, and tolerates inhibitory compounds 2-furaldehyde (furfural) and 5-hydroxymethyl-2-furaldehyde (HMF) associated with lignocellulose-to-fuel conversion. It produces three forms of β-glucosidase isozymes, BGL1, BGL2, and BGL3, and ferment cellobiose as the sole carbon source. These β-glucosidases exhibited desirable enzyme kinetic parameters and high levels of enzyme-specific activity toward cellobiose and many oligosaccharide substrates. They tolerate the product inhibition of glucose and ethanol, and are stable to temperature and pH conditions. These characteristics are desirable for more efficient cellulosic ethanol production by simultaneous saccharification and fermentation. NRRL Y-50464 provided the highest cellulosic ethanol titers and conversion rates at lower cellulase loadings, using either pure cellulose or agricultural residues, as so far reported in the literature. This review summarizes NRRL Y-50464 performance on cellulosic ethanol production from refined cellulose, rice straw, and corn stover processed in various ways, in the presence or absence of furfural and HMF. This dual functional yeast has potential to serve as a prototype for the development of next-generation biocatalysts. Perspectives on continued strain development and process engineering improvements for more efficient cellulosic ethanol production from lignocellulosic materials are also discussed.
Integrated Maximum Power Point Tracking System for Photovoltaic Energy Harvesting Applications

The integrated circuits employed for power management in photovoltaic (PV) energy harvesting applications are required to perform an efficient maximum power point tracking (MPPT) process for maximizing the power production of the PV source during the continuously changing atmospheric conditions. Among the alternative MPPT methods, the perturbation and observation (P&O) technique has the advantages of operational and implementation simplicity. In this article, a novel PV MPPT control system for on-chip implementation of the P&O MPPT method is presented, which, compared to the past-proposed on-chip MPPT systems, has the advantage that it is implemented based on purely digital CMOS circuits without requiring the use of complex circuits, such as multipliers, sample and hold units, or analog-to-digital converters. Therefore, it can be easily implemented on-chip with low design complexity while simultaneously retaining the high-performance features of the P&O MPPT technique. The proposed PV MPPT system has been fabricated using the XFAB XH018 0.18-μm CMOS technology. The experimental results verify the successful operation of the on-chip PV MPPT control unit and its ability to achieve a high MPPT efficiency over a wide range of operating solar irradiation values.
Diagnostic Accuracy of Contrast-Enhanced, Spectral Mammography (CESM) and 3T Magnetic Resonance Compared to Full-Field Digital Mammography plus Ultrasound in Breast Lesions: Results of a (Pilot) Open-Label, Single-Centre Prospective Study

Simple Summary The characterization of breast lesions by magnetic resonance imaging (MRI) is influenced by a high rate of false positives. Contrast-enhanced spectral mammography (CESM) is a promising modality that seems to compensate for the high costs, times and main limitations of MRI. The aim of our prospective study was to evaluate the diagnostic accuracy of CESM in comparison to 3T MRI imaging in the characterization of breast lesions. We enrolled 118 patients and histologically assessed 142 breast lesions. Patients underwent full-field digital mammography (FFDM), ultrasound (US), with CESM and MRI assessing the diagnostic accuracy of CESM. Sensitivity (Se), specificity (Sp), positive predictive value (PPV) and negative predictive value (NPV) were considered as measures of accuracy of different diagnostic procedures in predicting the nature and characteristics of the examined breast lesions. Abstract Introduction: To assess the diagnostic accuracy of CESM and 3T MRI compared to full-field digital mammography (FFDM), plus US, in the evaluation of advanced breast lesions. Materials and Methods: Consenting women with suspicious findings underwent FFDM, US, CESM and 3T MRI. Breast lesions were histologically assessed, with histology being the gold standard. Two experienced breast radiologists, blinded to cancer status, read the images. Diagnostic accuracy of (1) CESM as an adjunct to FFDM and US, and (2) 3T MRI as an adjunct to CESM compared to FFDM and US, was assessed. Measures of accuracy were sensitivity (Se), specificity (Sp), positive predictive value (PPV) and negative predictive value (NPV). Results: There were 118 patients included along with 142 histologically characterized lesions. K agreement values were 0.69, 0.68, 0.63 and 0.56 for concordance between the gold standard and FFDM, FFDM + US, CESM and MRI, respectively (p < 0.001, for all). K concordance for CESM was 0.81 with FFDM + US and 0.73 with MRI (p value < 0.001 for all). Conclusions: CESM may represent a valuable alternative and/or an integrating technique to MRI in the evaluation of breast cancer patients.
Ag Decoration and SnO2 Coupling Modified Anatase/Rutile Mixed Crystal TiO2 Composite Photocatalyst for Enhancement of Photocatalytic Degradation towards Tetracycline Hydrochloride

The anatase/rutile mixed crystal TiO2 was prepared and modified with Ag decoration and SnO2 coupling to construct a Ag@SnO2/anatase/rutile composite photocatalytic material. The crystal structure, morphology, element valence, optical properties and surface area were characterized, and the effects of Ag decoration and SnO2 coupling on the structure and photocatalytic properties of TiO2 were studied. Ag decoration and SnO2 coupling are beneficial to reduce the recombination of photogenerated electrons and holes. When the two modification are combined, a synergistic effect is produced in suppressing the photogenerated charge recombination, making Ag@SnO2/TiO2 exhibits the highest quantum utilization. After 30 min of illumination, the degradation degree of tetracycline hydrochloride (TC) by pure TiO2 increased from 63.3% to 83.1% with Ag@SnO2/TiO2.
Estudo Exploratório através de Análises Longitudinais aplicado à Ciência da Computação a partir da Base de Dados do ENADE

Em busca da qualidade na educação, diversas pesquisas no âmbito educacional são realizadas, no entanto, análise de grandes bases de dados em busca de informações úteis é uma tarefa desafiadora. Nesta pesquisa, foram identificados aspectos relacionados ao desempenho acadêmico dos alunos, utilizando como base as provas do ENADE aplicados ao curso de Ciência da Computação. A pesquisa foi regida pela metodologia que tange o Estudo Longitudinal Transversal Repetido, buscando analisar os dados ao longo do tempo, para verificar seu comportamento nos anos estudados. Os anos analisados foram 2011, 2014 e 2017. Foram aplicadas técnicas de mineração de dados nos microdados fornecidos pelo Instituto Nacional de Estudos e Pesquisas Educacionais Anísio Teixeira. A contribuição desta pesquisa é mostrar que dentre os algoritmos utilizados nos experimentos, o que melhor classificou os dados em relação ao desempenho dos alunos foi a árvore de decisão, a qual possibilitou identificar que algumas características socioeconômicas como por exemplo renda familiar, escolaridade do pai, situação de trabalho do discente em conjunto com a categoria administrativa e o turno de graduação impactam no desempenho acadêmico.
Stability and power sharing in microgrids

Motivated by environmental, economic and technological aspects, the penetration of renewable energy sources into the electrical networks is increasing worldwide. This fact requires a paradigmatic change in power system operation. One solution to facilitate this change are microgrids. In the present work, the problems of frequency stability, voltage stability and power sharing in microgrids are considered. More precisely, control concepts that address the aforementioned problems are investigated. The main contributions of the present work comprise: (i) A generic modular model of an uncontrolled microgrid is derived. (ii) A consensus-based distributed voltage control (DVC) is proposed, which guarantees a desired reactive power distribution in steady-state. In contrast with other control strategies available thus far, the control presented in this work only requires distributed communication among generation units, i.e., no central computing nor communication unit is needed. (iii) Conditions for local asymptotic stability of several microgrid configurations are derived. The considered networks comprise inverter-based microgrids operated with frequency and voltage droop control, as well as microgrids operated with frequency droop control and the proposed DVC. The conditions are established via converse Lyapunov theorems in combination with tools from linear algebra, as well as port-Hamiltonian systems. Most conditions are derived under the assumption of dominantly inductive power lines. (iv) Conditions are given under which the frequency droop control, respectively the proposed DVC, solve the problem of active, respectively reactive, power sharing in microgrids with dominantly inductive power lines. The claims are established by combining the aforementioned stability results with a design criterion for the controller gains and setpoints of the frequency droop control, respectively with the inherent properties of the DVC. (v) The analysis is validated via simulation on a microgrid based on the CIGRE benchmark medium voltage distribution network.
Exploratory study on an innovative use of cosmic-ffp for early quality assessment

The functional size measurement method, COSMIC-FFP, adopted as the ISO/IEC 19761 standard in 2003, was developed by the Common Software Measurement International Consortium (COSMIC). It focuses on the "user view" of functional requirements and is applicable throughout the development life cycle. As some of the software systems targeted by COSMIC-FFP are large-scale and inherently complex, feedback on their functional complexity would facilitate containment of that complexity throughout the software life cycle. In this thesis, a new early quality assessment of COSMIC-FFP models is proposed. The benefits of this work include earlier prediction of the functional complexity of the behavior of software in the COSMIC-FFP context, right from the requirements phase, as well as a mechanism for generating black-box test cases from the COSMIC-FFP model, test case prioritization and test set adequacy monitoring and optimization within given budget constraints, and an early prediction of reliability based on Markov chains. We also present a study of the scales, units and scale types of both COSMIC-FFP and the Entropy-based Functional Complexity Measure that forms the basis of the testing assessment method we propose here. Previous studies have analyzed the scale types of many pieces of software, but not the concept of scale itself, nor how it is used in the design of a measurement method. Two well-known case studies are introduced to demonstrate the applicability of the proposed methods: the Hotel Accommodation System and the Railroad System. We include a formalized COSMIC-FFP definition in the AS-TRM context (Autonomic Systems Timed Reactive Object Model), a language for the formal design of autonomic reactive systems developed at Concordia University. We introduce the Steam Boiler case study to demonstrate the applicability of formalizing COSMIC-FFP in the AS-TRM context. Future work based on this thesis can include the development of AS-TRM specifications for several benchmark case studies, and the collection of COSMIC-FFP measurement data for both the theoretical and empirical validation of the proposed measurement method. The testing method proposed here has been adapted to a specific class of projects, namely Enterprise Resource Planning (ERP) projects, which are perceived to be mission-critical initiatives in many organizations. They can be found in business transformation programs and are instrumental in improving organizational performance.
Beamforming OLEDs for sensing applications employing a nanostructured fluorescent waveguide layer

Organic light-emitting diodes (OLEDs) hold great promise as light sources for miniaturized and monolithically integrated optical sensors. Their unique properties and flexible processing methods enable the realization of disposable or recyclable lab-on-a-chip systems by combining multiple light sources and detector units on a single substrate. One of the main challenges in these systems is tailoring of light emission characteristics in order to illuminate specific sensing spots without the use of external optical components. Since OLEDs typically exhibit wide-angle light emission across the device surface, we propose the implementation of a nanostructured fluorescent waveguide. This layer acts as a color conversion filter by absorbing OLED light while providing narrow-angle emission of fluorescent light propagating in the waveguide. The appropriate choice of OLED emission color, fluorescent dye and nanostructure design allows for tailoring of the emission wavelength and beam characteristics. We investigate the impact of various fabrication parameters such as the layer thickness and fluorophore concentration on the color conversion efficiency as well as the directionality of the outcoupled fluorescent light. While high absorption of the OLED excitation light is beneficial in order to suppress wide-angle background emission, we show that high fluorophore content may lead to fluorescence quenching and reabsorption of fluorescent light inside the waveguide impairing resonant outcoupling effects.