Miracle-dz/UniFAR-FTUs huggingface dataset:
Validation of the EEG signal of the URGOnight neurofeedback device, associated with a new SMR detection method

Sensorimotor (SMR) neurofeedback is a promising therapy for several health disorders but is still not widely used due to the high cost of the equipment. URGOnight offers a low-cost solution to democratize these therapies by providing an at-home EEG headband with dry electrodes connected to a mobile application. The first aim of this study is both to validate the URGOnight EEG signal and to compare it to Enobio-20, a medical grade EEG device. The second aim of the study is to propose a new method to detect SMR rhythm based on its oscillatory properties and discriminate it from alpha oscillations. In our study, we compared the URGOnight headband EEG signal (C3/C4) to Enobio-20 (CP3/CP4), placed on subjects simultaneously equipped with the two headbands. All subjects (n=33) performed a dual blocking task inspired by Kulhman (1978) based on the blocking effect of movement and eyes opening on SMR and alpha respectively. This task was followed by SSVEP stimulations to evaluate the frequency response of the two EEG devices. The performance of the EEG headbands was statistically identical for most of the characteristics of the EEG signal, including the frequency response to SSVEP (from 4Hz to 20Hz). The main difference was a larger amplitude in the 8-15Hz due to the location of the reference in URGOnight that did not impair the detection of both alpha and SMR. In addition, we show that our new method allows to discriminate alpha and SMR rhythms based on their oscillatory properties with a single recording site (C3/C4). The method is fast enough to be used in real time. We show that the detected SMR rhythm is modulated by movement as opposed to the 12-15Hz frequency band often used as indicator of SMR in most neurofeedback studies. Altogether, our results validate the quality of the EEG recordings obtained with URGOnight since it gives similar results as the one obtained with Enobio-20, a validated EEG medical grade system. In addition, we provide a new method allowing the identification and the separation of the alpha and SMR with a single recording site C3/C4. This method opens up a new research lead to improve SMR neurofeedback efficiency and thus of its clinical possibilities by focusing on the reinforcement of the SMR oscillation strictly speaking. Highlights - Validation of the URGOnight EEG device suitable for neurofeedback at home - New method for the detection and the discrimination of alpha rhythm and SMR rhythm with a small number of recording sites - The oscillatory activity related to the SMR displays different properties compared to the 12-15Hz frequency band. - Description of a full validation procedure for wireless EEG devices usable at home for neurofeedback - Comparison of the signal of URGOnight (dry electrodes) with a wet electrode EEG device
Title: Tracing diurnal differences in brain anatomy with voxel-based morphometry - associations with sleep characteristics and data quality

In recent decades magnetic resonance imaging (MRI) has established itself as the golden standard for studying human brain structure. As a result, it has become increasingly more important to identify technical and physiological factors that may influence study outcomes and contribute to misleading conclusions. This work set out to investigate and compare the variability in voxel-based morphometry (VBM) associated with data quality and time-of-day (TOD) when images are collected using a large longitudinal dataset (N = 72). To test the replicability of the results connected to each factor, the analyses were conducted in two comparable cohorts (each N = 36). The replicated TOD differences were further tested for their correlation with indices of sleep. We report that TOD is a significant and partially replicable predictor of the variability in VBM with the magnitude of the observed differences regionally connected to sleep length. Although data quality also has a prevalent impact on VBM, the affected areas were inconsistent across the two datasets. Interestingly, certain overlapping regions were identified in both analyses, showing that longitudinal results could be misattributed to image quality unless this factor is accounted for. All in all, both TOD and data quality are crucial variables to be considered and controlled for at the stage of experimental planning, as well as data acquisition and analysis. Inclusion of these parameters in the study designs can greatly improve the reliability and replicability of the reported MRI results.
VAD in Speech Coder Based on Wavelet Transform

One of the methods of reducing the data flow in packet transmission of speech is to exclude those speech packets that do not carry enough information. This leads to the use of the systems VoIP (Voice over IP) or voice transmission technologies by IP (Internet Protocol – IP) a new type of voice signal encoders – with a variable encoding speed. The functions of detecting packets with a small voice load are carried by nodes with the standard name Voice Activity Detector (VAD). The main difficulty in the synthesis of VAD for VoIP speech signal encoders is the correct detection of speech pauses against a background of sufficiently intense acoustic noise (office, street, car noise, etc.). However, the use of VAD makes it possible to significantly save the bandwidth of a distributed network.
Domain Ontology Learning using Link Grammar Parser and WordNet

The problem of knowledge discovery that comes down to information pertinence evaluation still stay unsolved because of absence of practical effective methods and means of ontology learning. Despite active development of natural language processing tools, they mostly reach the level of semantics, named entity recognition and sentiment analysis but not pragmatics. On the other hand, ontology is the only instrument, “measuring ruler” to compare and estimate the usefulness of information for some particular user, which knowledge could be represented by such ontology as his hierarchical task network (HTN). The need to build separate HTN ontology for each user puts on the agenda the task of design of the automated ontology learning from text. With aim to solve this task the system of automated and semi-automated ontology learning from text had been developed using Carnegie Mellon Link Grammar Parser and WordNet API. Two approaches to distinguish semantic relations in natural language text (NLT) sentences were adopted: analysis of the sentence constituent trees – for explicit relations recognition and Naïve Bayes supervised learning – for recognition implicit semantic relations which need not only verb phrase but other parts of sentence due to its ambiguity. Developed approach was implemented in the Java desktop application using OWL API and Protégé-OWL API. Experimental results were compared to expert analysis and had shown good recognition reliability.
Features of designing and implementing an information system for studying and determining the level of foreign language proficiency

This article analyzes the existing methods, international certifications and known systems that provide tools for learning foreign languages and describes the mechanisms for assessing these skills, which revealed the main shortcomings of existing approaches and showed the relevance of the study. The main requirements for the systems of this class are identified and presented in the form of work scenarios on the example of the module Learning Materials, which is presented to users with the roles of "Teacher" and "Student". A mathematical description of the subject area using the algebra of algorithms, which provided the means to minimize the created models by the number of uniterms. The presented models give a complete picture of the features of the system. The software system was designed using an object-oriented approach and the created diagrams were displayed in accordance with the UML notation. The study presents diagrams of options for use and activities, which simplified the understanding of the features of the information system of learning and determining the level of knowledge of foreign languages. The result of the study was the design and implementation of a system using the Golang programming language. Natural language processing is implemented in a separate module that provides tokenization and parsing, lemmatization / stemming, tagging of a part of speech and identification of semantic connections. The created software product works in the prototype mode and implements the described functionality.
Models and means of object recognition using artificial neural networks

The purpose of this work is to present a generalized approach for object detection using neural networks in various environments. The novelty of the research is an offered combination of the machine learning method – neural network for object detection and the classical method – custom programmed algorithm for selecting objects of our interest. The effectiveness of the approach is achieved by combining the two methods and using their strengths – ability of neural networks to learn from images dataset and work with new images and ability to deliver unique business value using custom programmed algorithms. This paper describes solving this problem, finding the necessary methods and algorithms.
Advanced Method of Synthesis of Semantic Kernel of E-content

The work describes an improved method of synthesis of the semantic kernel of e-content. This method is an integral part of the new technology of virtual promotion of goods and services. This technology is an alternative way to solve the problem of search engine optimization on the Internet. Its main components are the semantic kernel and the progress map. The previously obtained results of the execution of WEB projects of virtual promotion show that the correct choice of the semantic kernel gives an improvement of the main WEB metrics tenfold. Therefore, solving the problem of nuclear synthesis is an urgent problem. In this article, a synthesis method is proposed, which is based on a text model that includes aspect terms and collocations. The algorithm and results of ego application in a real WEB project for the virtual promotion of online services in the US market are also presented.
RESEARCH OF METHODS AND MEANS OF ENSURING THE RELIABILITY OF A SPECIALIZED COMPUTER VOICE VEHICLE CONTROL SYSTEM

The methods and means of protection of reliability in modern specialized computer systems of voice control of the car are investigated in the work. The evaluation of the characteristics and properties of the system is carried out. The basic principles of work and various possibilities of constructions of voice control of the car are considered. The methods and means of detecting dangers are shown, and the shortcomings and vulnerabilities of the car systems "Android Auto" and "Apple CarPlay" regarding the impact of malicious software based on modern methods of cyberattacks are identified. Preparation for cyber attack by ultrasonic and light commands on car voice control systems is shown. Methods and means for increasing the degree of protection of the voice authentication system of specialized computer systems "Android Auto" and "Apple CarPlay" are proposed. To solve this problem, a hardware and software product of an additional biometric automotive user authentication system was created and developed. The system was created to ensure the reliability of cyber attacks on the voice control system. Experimental studies confirm the effectiveness of the biometric authentication system as a proposed solution to provide an additional method of protection.
DESIGN OF DATA BUFFERS IN FIELD PROGRAMMABLR GATE ARRAYS

Annotation: The design of the data buffers for the field programable gate array (FPGA) projects is considered. A new method of buffer design is proposed, which is based on the representation of the synchronous dataflow graph in the three-dimensional space, optimization of them, and description in VHDL. The method gives the optimized buffers which are based either on RAM or on the register pipeline. The derived pipeline buffer can be mapped into the shift register primitive of FPGA. The method is built in the experimental SDFCAD framework intended for the pipelined datapath synthesis.
Functionalization of single-walled carbon nanotubes with ribonucleic acids

The optical properties of single-walled carbon nanotubes (SWCNTs) dispersed in aqueous solutions of ribonucleic acids (RNA) purified from Escherichia coli were studied using photoluminescence (PL), Raman, and absorption spectroscopy. SWCNT-RNA complexes, down to a single isolated nanotube level, were successfully synthesized. SWCNT signatures in Raman, PL, and absorption spectroscopy were observed from the SWCNT-RNA complexes. Observation of two distinct PL peaks, one at 1.248 eV and the other at 1.392 eV, confirmed the existence of isolated (6,5) and (6,4) SWCNTs, respectively. Atomic force microscope images and height profiles also showed evidence of isolated SWCNT-RNA complex.
Efficacy and safety of acupuncture in combination with Chinese herbal medicine in dealing with osteoporosis: A protocol for a systematic review and network meta-analysis

Background: Osteoporosis (OP) has emerged as a major global public health issue due to its high prevalence, unknown pathogenesis, and lack of specific drugs for prevention and treatment. Studies have demonstrated that acupuncture in combination with Chinese herbal medicine (CHM) is effective in treating OP. However, there is a scarcity of experience and high-quality evidence. A network meta-analysis and systematic review were used to evaluate the efficacy and safety of acupuncture in combination with CHM for the treatment of OP. Methods: Comprehensive search of Chinese databases such as China National Knowledge Infrastructure, VIP, Wanfang, China Biomedical Literature Database and English databases for example PubMed, Cochrane Library, EMbase, etc. The search period was extended from the creation of the database to November 2022. All randomized controlled trials on acupuncture in combination with CHM in dealing with OP were collected. After literature analysis and data extraction, the Cochrance system was used to evaluate the high quality of the included articles and Stata 14.0 was used for the network meta-analysis. Results: The current systematic review and network meta-analysis will provide the effectiveness and safety of acupuncture in combination with CHM in dealing with OP. Conclusion: The research will provide reliable evidence for the clinical use of acupuncture in combination with CHM in dealing with OP.
Effect of intravenous antihypertensives on outcomes of severe hypertension in hospitalized patients without acute target organ damage

Background: Treatment of severe inpatient hypertension (HTN) that develops during hospitalization is not informed by guidelines. Intravenous (i.v.) antihypertensives are used to manage severe HTN even in the absence of acute target organ damage; however they may result in unpredictable blood pressure (BP) reduction and cardiovascular events. Our goal was to assess the association between i.v. antihypertensives and clinical outcomes in this population. Methods: This is a multihospital retrospective study of adults admitted for reasons other than HTN who develop severe HTN during hospitalization without acute target end organ damage. We defined severe HTN as BP elevation of systolic >180 or diastolic >110 mmHg. Treatment was defined as receiving i.v. antihypertensives within 3 h of BP elevation. We used overlap propensity score weighted Cox models to study the association between treatment and clinical outcomes during index hospitalization. Results: Of 224 265 unique, nonintensive care unit hospitalizations, 20 383 (9%) developed severe HTN, of which 5% received i.v. antihypertensives and 79% were untreated within 3 h of severe BP elevation. In the overlap propensity weighted population, patients who received i.v. antihypertensives were more likely to develop myocardial injury (5.9% in treated versus 3.6% in untreated; hazard ratio [HR]: 1.6 [1.13, 2.24]). Treatment was not associated with increased risk of stroke (HR: 0.7 [0.3, 1.62]), acute kidney injury (HR: 0.97 [0.81, 1.17]), or death (HR: 0.86 [0.49, 1.51]). Conclusions: Intravenous antihypertensives were associated with increased risk of myocardial injury in patients who develop severe HTN during hospitalization. These results suggest that i.v. antihypertensives should be used with caution in patients without acute target organ damage.
LncRNA LOXL1-AS1 expression in cancer prognosis: A meta-analysis

Background: Several studies showed that LncRNA LOXL1 antisense RNA 1 (LOXL1-AS1) is overexpressed in a variety of cancers and plays a role as an oncogene in cancer. The present meta-analysis aims to elucidate the relationship between LOXL1-AS1 expression and prognosis and clinicopathological features among cancer patients. Methods: PubMed, Web of Science, Cochrane Library, and EMBASE database were comprehensively and systematically searched. Pooled odds ratios (ORs) and hazard ratios with a 95% confidence interval (CI) were employed to assess the relationship between LOXL1-AS1 expression and clinical outcomes and clinicopathological features in cancer patients. Results: The present study finally enrolled 8 studies which included 657 cancer patients. The combined results indicated that the overexpression of LOXL1-AS1 was significantly associated with shorter overall survival (pooled hazard ratio = 1.99, 95% CI 1.49–2.65, P < .00001). Meanwhile, regarding clinicopathology of cancer patients, the upregulation of LOXL1-AS1 expression was closely related to lymph node metastasis (yes vs no OR = 4.01, 95% CI: 2.02–7.96, P < .0001) and distant metastasis (yes vs no OR = 3.04, 95% CI: 1.82–5.06, P < .0001), respectively. Conclusion: High expression of LOXL1-AS1 in some cancers predicts shorter overall survival, distant metastasis, and lymph node metastasis. LOXL1-AS1 shows great promise as a prognostic biomarker in cancer patients.
Effects of Implementing a Self-Care Program for Adults With Lower Limb Prostheses

An artificial replacement for a lost limb or portion of a limb, known as a prosthesis, is a tool that can assist a person to regain their independence. The aim of this project was to evaluate the effect of a self-care program for adults with lower limb prostheses. We used a quasi-experimental research design. We conducted our study at the Physical Medicine and Rehabilitation and Rheumatology Center affiliated with the Armed Forces, located in the Al-Geza Governorate of Egypt using a purposeful sample of 81 adults with lower limb prostheses. We used two tools for data collection: a structured interviewing questionnaire and the Trinity Amputation and Prosthesis Experience Scales (TAPES). The mean age of adults with lower limb prosthesis in our study was 38.91 years (10.53). A total of 64.2% of the study participants (n = 51) were men. We found that before the self-care program, 22.2% of the participants (n = 18) had a satisfactory level of knowledge about self-care, which increased to 88.9% (n = 72) after the program. Before the self-care program, the number of participants with adequate practice levels was 13.6% (n = 11), which increased to 100.0% (n = 81) after the program. We concluded that implementing the self-care program provided a significant improvement in the attendee's total satisfactory knowledge (χ2[79,81] = 72.90, p < .000) and adequate practice levels (p < .001).
Remotely monitored Baduanjin exercise in moderate-to-severe chronic obstructive pulmonary disease patients (BROCADE): A study protocol

Background: Baduanjin is a traditional Chinese exercise regimen used to treat various chronic illnesses and is associated with both psychological and physical benefits. However, its benefits for patients suffering from chronic obstructive pulmonary disease (COPD) are unclear. This study aims to assess the efficacy, safety, and underlying mechanisms of Baduanjin exercise in patients with moderate-to-severe COPD (BROCADE) by remote monitoring. Methods: This study protocol describes a multicenter, open-label, prospective randomized computed tomography. A total of 150 individuals who meet the inclusion criteria after the screening and consent processes will take part in the study. All participants will be provided routine medication and lifestyle interventions. They will be randomly assigned to a control group, a classical pulmonary rehabilitation group, or a Baduanjin group, which will undergo remotely monitored Baduanjin exercises for a cumulative duration of 1 hour per day, three times per week for 12 weeks. The participants will be followed for 24 weeks. The primary outcomes will be a 6-minutes walking distance and St. George’s Respiratory Questionnaire index. The secondary outcomes will be lung function, cross-sectional area of the pectoralis major and subcutaneous fat, modified Medical Research Council score, COPD assessment test questionnaire results, extremity muscle strength, and quality of life. Any adverse events that may occur will be monitored and recorded. Results: This study is ongoing and will be submitted to a peer-reviewed journal for publication once completed. Conclusion: A novel neutrophil-related inflammatory mechanism will potentially be identified. In addition, the study results will provide a safe, effective, simple and operational Baduanjin exercise protocol for moderate-to-severe COPD patients aimed at improving prognosis and quality of life.
Association between polymorphisms in miRNAs and ischemic stroke: A meta-analysis

Background: Atherosclerosis remains a predominant cause of ischemic stroke (IS). Four miRNA polymorphisms associated with arteriosclerosis mechanism were meta-analyzed to explore whether they had predictive significance for IS. Methods: PubMed, Excerpta Medica database, Web of Science, Cochrane Library, Scopus, China National Knowledge Infrastructure, and China Wanfang Database were searched for relevant case-control studies published before September 2022. Two researchers independently reviewed the studies and extracted the data. Data synthesis was carried out on eligible studies. Meta-analysis, subgroup analysis, sensitivity analysis, and publication bias analysis were performed using Stata software 16.0. Results: Twenty-two studies were included, comprising 8879 cases and 12,091 controls. The results indicated that there were no significant associations between miR-146a C>G (rs2910164), miR-196a2 T>C (rs11614913) and IS risk in the overall analyses, but miR-149 T>C (rs2292832) and miR-499 A>G (rs3746444) increased IS risk under the allelic model, homozygote model and recessive model. The subgroup analyses based on Trial of Org 101072 in Acute Stroke Treatment classification indicated that rs2910164 increased small artery occlusion (SAO) risk under the allelic model, heterozygote model and dominant model; rs11614913 decreased the risk of SAO under the allelic model, homozygote model, heterozygote model and dominant model. Conclusion: This Meta-analysis showed that all 4 single nucleotide polymorphisms were associated with the risk of IS or SAO, even though the overall and subgroup analyses were not entirely consistent.
Continual Learning for medical image classification

Continual Learning (CL) is a novel paradigm in which the trained model is computed via a stream of data where tasks and data are only available over-time. Indeed, such approaches are able to learn new skills and knowledge without forgetting the previous ones: no access to previously encountered data and mitigate catastrophic forgetting. In this work, we propose a comparison of different CL algorithms in performing the classification of medical images. In particular, we aim to highlight the potential and ability of current methods in preventing catastrophic forgetting of the previous tasks when a new one is learned. CL-based methods have been tested for the classification of medical images showing the viability and effectiveness of these approaches.