Miracle-dz/UniFAR-FTUs huggingface dataset:
Speed of Processing and Personality: The Influence of Personality and Extrinsic Feedback on the Performance of Cognitive Tasks

Background: Feedback is considered as an effective means of motivating, guiding, and reinforcing desired behaviours. However, the ways to interpret external feedback may be different among individuals with different personality traits; therefore, this would influence the effects of feedback on performance. Accordingly, the influencing effects of personality towards different styles of feedback on cognitive task performance were examined. Methods: Participants (N = 71) were given three Stroop tasks as a dependent variable, whereas the Trail Making Task was an independent variable; additionally, a personality test was used to record the personality traits of each participant. The relationship between personality and feedback-induced changes in Stroop performance was computed by means of Pearson correlation, followed by a mixed-effect model to demonstrate the effect of personality on the overall performance with feedback. Results: The statistical analysis indicated that performance from those with higher levels of extraversion generally profitted from feedback, irrespective of whether it was negative feedback (r = 0.201) or positive feedback (r = 0.205). Additionally, the moderating effect of personality on feedback and performance was demonstrated. Conclusions: The limitations of the sample size and other external influences may have reduced the representativeness of the research. Nonetheless, more potential influencing factors need to be included and explored in future research.
Host–Parasite: Graph LSTM-in-LSTM for Group Activity Recognition

This article aims to tackle the problem of group activity recognition in the multiple-person scene. To model the group activity with multiple persons, most long short-term memory (LSTM)-based methods first learn the person-level action representations by several LSTMs and then integrate all the person-level action representations into the following LSTM to learn the group-level activity representation. This type of solution is a two-stage strategy, which neglects the “host–parasite” relationship between the group-level activity (“host”) and person-level actions (“parasite”) in spatiotemporal space. To this end, we propose a novel graph LSTM-in-LSTM (GLIL) for group activity recognition by modeling the person-level actions and the group-level activity simultaneously. GLIL is a “host–parasite” architecture, which can be seen as several person LSTMs (P-LSTMs) in the local view or a graph LSTM (G-LSTM) in the global view. Specifically, P-LSTMs model the person-level actions based on the interactions among persons. Meanwhile, G-LSTM models the group-level activity, where the person-level motion information in multiple P-LSTMs is selectively integrated and stored into G-LSTM based on their contributions to the inference of the group activity class. Furthermore, to use the person-level temporal features instead of the person-level static features as the input of GLIL, we introduce a residual LSTM with the residual connection to learn the person-level residual features, consisting of temporal features and static features. Experimental results on two public data sets illustrate the effectiveness of the proposed GLIL compared with state-of-the-art methods.
Exploring Beliefs About Exercise Among Pregnant Women in Rural Communities.

INTRODUCTION Women who are pregnant in rural communities are disproportionally impacted by obesity and sedentary behavior, and this could be related to having negative beliefs about exercise during pregnancy, leading to inactivity. The purpose of this study was to identify self-reported beliefs about exercise among pregnant women in a rural community. METHODS Pregnant participants (N = 70) between 8 and 16 weeks' gestation were recruited from an obstetric clinic serving a rural population. An open-ended questionnaire addressing beliefs about exercise and based on the constructs of the theory of planned behavior was administered. Descriptive survey results were analyzed by calculating means and frequencies. Open-ended responses were assessed by inductive content analysis. RESULTS Commonly reported advantages of exercise during pregnancy included improved perinatal health outcomes and weight management. Commonly reported disadvantages included an increase in fatigue and concerns for maternal and fetal safety. Common facilitators of exercise included access to resources, free time or a decrease in demands from work, and support systems including family and friends. Common barriers to exercise included a lack of time, physical changes including feelings of nausea and fatigue, and lack of access to resources. DISCUSSION This study was the first to report beliefs about exercise during pregnancy in a rural setting. Responses in the current study suggest potential gaps in knowledge of evidence-based information regarding physical activity during pregnancy. Beliefs as well as reported barriers and facilitators of physical activity during pregnancy were similar those reported in other populations. In addition, access to resources (or lack of) appears to be an important facilitator (or barrier) among women in rural settings; thus, developing strategies designed to overcome this barrier, specifically in rural areas, is critically important. Future intervention strategies need to be tailored specifically to the needs of women living in rural areas.
Fuzzy-Based Concept Learning Method: Exploiting Data With Fuzzy Conceptual Clustering

Concepts have been adopted in concept-cognitive learning (CCL) and conceptual clustering for concept classification and concept discovery. However, the standard CCL algorithms are incapable of tackling continuous data directly, and some standard conceptual clustering methods mainly focus on the attribute information, ignoring the object information that is also important to improve clustering analysis and concept classification ability. Therefore, in this article, we present a novel concept learning method, called the fuzzy-based concept learning model (FCLM), to address these two issues by exploiting concept hierarchical relations in concept lattices. More specifically, we first show some new related notions for FCLM based on a regular fuzzy formal decision context; among these notions, the object-oriented and attribute-oriented fuzzy concept similarities are used to achieve the concept similarity measure in concept lattices. Moreover, a novel fuzzy concept learning framework is designed, and its corresponding learning algorithms are developed. Finally, we conduct some experiments on various real-world datasets to demonstrate that the proposed method can achieve the state-of-the-art classification performance among similarity-based learning methods. In addition, we further verify the effectiveness of our method in concept discovery on the MNIST dataset.
Circulating miR-320a as a Predictive Biomarker for Left Ventricular Remodelling in STEMI Patients Undergoing Primary Percutaneous Coronary Intervention

Restoration of epicardial coronary blood flow, achieved by early reperfusion with primary percutaneous coronary intervention (PPCI), is the guideline recommended to treat patients with ST-segment-elevation myocardial infarction (STEMI). However, despite successful blood restoration, increasing numbers of patients develop left ventricular adverse remodelling (LVAR) and heart failure. Therefore, reliable prognostic biomarkers for LVAR in STEMI are urgently needed. Our aim was to investigate the role of circulating microRNAs (miRNAs) and their association with LVAR in STEMI patients following the PPCI procedure. We analysed the expression of circulating miRNAs in blood samples of 56 patients collected at admission and after revascularization (at 3, 6, 12 and 24 h). The associations between miRNAs and left ventricular end diastolic volumes at 6 months were estimated to detect LVAR. miRNAs were also analysed in samples isolated from peripheral blood mononuclear cells (PBMCs) and human myocardium of failing hearts. Kinetic analysis of miRNAs showed a fast time-dependent increase in miR-133a, miR-133b, miR-193b, miR-499, and miR-320a in STEMI patients compared to controls. Moreover, the expression of miR-29a, miR-29b, miR-324, miR-208, miR-423, miR-522, and miR-545 was differentially expressed even before PPCI in STEMI. Furthermore, the increase in circulating miR-320a and the decrease in its expression in PBMCs were significantly associated with LVAR and correlated with the expression of miR-320a in human failing myocardium from ischaemic origin. In conclusion, we determined the time course expression of new circulating miRNAs in patients with STEMI treated with PPCI and we showed that miR-320a was positively associated with LVAR.
Mechanical, Electrical, and Piezoresistive Sensing Characteristics of Epoxy-Based Composites Incorporating Hybridized Networks of Carbon Nanotubes, Graphene, Carbon Nanofibers, or Graphite Nanoplatelets

The present study compared the mechanical, electrical, morphological, and piezoresistive characteristics of epoxy-based sensing nanocomposites fabricated with inclusions of hybridized networks of four different carbon nanomaterials (CNMs), such as carbon nanotube (CNT), graphene, carbon nanofiber (CNF), and graphite nanoplatelet (GNP). Enhancements in elastic modulus and electrical conductivity were achieved by CNT–graphene composites and CNT–CNF composites, and these were explained by the morphological observations carried out in the present study and experimental studies found in the literature. The greatest gauge factor was accomplished by the CNT–GNP composite, followed by the CNT–CNF composite among composites where the CNM networks were sufficiently formed with a content ratio of 3%. The two types of the composites outperformed the composites incorporating solely CNT in terms of gauge factor, and this superiority was explained with the excluded volume theory.
Effects of Particulate Matter on the Incidence of Respiratory Diseases in the Pisan Longitudinal Study

The current study aimed at assessing the effects of exposure to Particulate Matter (PM) on the incidence of respiratory diseases in a sub-sample of participants in the longitudinal analytical epidemiological study in Pisa, Italy. Three hundred and five subjects living at the same address from 1991 to 2011 were included. Individual risk factors recorded during the 1991 survey were considered, and new cases of respiratory diseases were ascertained until 2011. Average PM10 and PM2.5 exposures (µg/m3, year 2011) were estimated at the residential address (1-km2 resolution) through a random forest machine learning approach, using a combination of satellite data and land use variables. Multivariable logistic regression with Firth’s correction was applied. The median (25th–75th percentile) exposure levels were 30.1 µg/m3 (29.9–30.7 µg/m3) for PM10 and 19.3 µg/m3 (18.9–19.4 µg/m3) for PM2.5. Incidences of rhinitis and chronic phlegm were associated with increasing PM2.5: OR = 2.25 (95% CI: 1.07, 4.98) per unit increase (p.u.i.) and OR = 4.17 (1.12, 18.71) p.u. i. , respectively. Incidence of chronic obstructive pulmonary disease was associated with PM10: OR = 2.96 (1.50, 7.15) p.u. i. These results provide new insights into the long-term respiratory health effects of PM air pollution.
Compassionate Use of Remdesivir for Patients with Severe Covid-19

Abstract Background Remdesivir, a nucleotide analogue prodrug that inhibits viral RNA polymerases, has shown in vitro activity against SARS-CoV-2. Methods We provided remdesivir on a compassionate-use basis to patients hospitalized with Covid-19, the illness caused by infection with SARS-CoV-2. Patients were those with confirmed SARS-CoV-2 infection who had an oxygen saturation of 94% or less while they were breathing ambient air or who were receiving oxygen support. Patients received a 10-day course of remdesivir, consisting of 200 mg administered intravenously on day 1, followed by 100 mg daily for the remaining 9 days of treatment. This report is based on data from patients who received remdesivir during the period from January 25, 2020, through March 7, 2020, and have clinical data for at least 1 subsequent day. Results Of the 61 patients who received at least one dose of remdesivir, data from 8 could not be analyzed (including 7 patients with no post-treatment data and 1 with a dosing error). Of the 53 patients whose data were analyzed, 22 were in the United States, 22 in Europe or Canada, and 9 in Japan. At baseline, 30 patients (57%) were receiving mechanical ventilation and 4 (8%) were receiving extracorporeal membrane oxygenation. During a median follow-up of 18 days, 36 patients (68%) had an improvement in oxygen-support class, including 17 of 30 patients (57%) receiving mechanical ventilation who were extubated. A total of 25 patients (47%) were discharged, and 7 patients (13%) died; mortality was 18% (6 of 34) among patients receiving invasive ventilation and 5% (1 of 19) among those not receiving invasive ventilation. Conclusions In this cohort of patients hospitalized for severe Covid-19 who were treated with compassionate-use remdesivir, clinical improvement was observed in 36 of 53 patients (68%). Measurement of efficacy will require ongoing randomized, placebo-controlled trials of remdesivir therapy. (Funded by Gilead Sciences.)
Guaranteed Cost Finite-Time Control of Uncertain Coupled Neural Networks

This article investigates a robust guaranteed cost finite-time control for coupled neural networks with parametric uncertainties. The parameter uncertainties are assumed to be time-varying norm bounded, which appears on the system state and input matrices. The robust guaranteed cost control laws presented in this article include both continuous feedback controllers and intermittent feedback controllers, which were rarely found in the literature. The proposed guaranteed cost finite-time control is designed in terms of a set of linear-matrix inequalities (LMIs) to steer the coupled neural networks to achieve finite-time synchronization with an upper bound of a guaranteed cost function. Furthermore, open-loop optimization problems are formulated to minimize the upper bound of the quadratic cost function and convergence time, it can obtain the optimal guaranteed cost periodically intermittent and continuous feedback control parameters. Finally, the proposed guaranteed cost periodically intermittent and continuous feedback control schemes are verified by simulations.
ERCC2 Lys751Gln rs13181 and XRCC2 Arg188His rs3218536 Gene Polymorphisms Contribute to Subsceptibility of Colon, Gastric, HCC, Lung And Prostate Cancer.

PURPOSE Cancer is the leading cause of death in economically developed countries and the second leading cause of death in developing countries. The relationship between genetic polymorphisms and cancer risk has been extensively researched. In the present study, we evaluated the association between polymorphisms in two DNA repair genes, ERCC2 Lys751Gln (rs13181) and XRCC2 Arg188His (rs3218536) and the risk of colorectal, stomach, HCC, prostate and lung cancer. METHODS This study was planned by the Medical Biology Unit and Department of Internal Medicine, Pathology and Surgical Medicine Sciences of Ataturk University. A total of 40 colon cancer, 40 gastric cancer, 40 hepatocellular carcinoma (HCC), 40 prostate cancer, and 40 lung cancer patients and 40 healthy individuals over 18 years of age were enrolled in the study (Controls). All patients and healthy subjects underwent ERCC2 Lys751Gln rs13181 and XRCC2 Arg188His rs3218536 genotyping. After collection of 10 ml venous blood from the patients, DNA was isolated and single nucleotide polymorphism (SNP) analysis was performed using Roche 480 Real-Time PCR device. Results were analyzed using SPSS version 23.0 software. RESULTS There were statistically significant differences in ERCC2 Lys751Gln rs13181 polymorphism variants GG colon and GT in the colon control and GG,TTprostate cancer groups when compared with the control group. GG variant of XRCC2 Arg188 rs3218536 was higher in the gastric patient group. AG variant of XRCC2 Arg188 rs3218536 was higher in gastric control group Conclusion: The results of the present study demonstrate that ERC22 Lys751Gln polymorphisms may be associated with the development of colon and prostate cancers in the Turkish population. This was a small-scale study, and the results should be corroborated with further research including larger groups of patients with each cancer type and more healthy controls.
Co-activation of rhythms during alpha band oscillations as an interictal biomarker of exploding head syndrome

Background Exploding head syndrome is a rarely reported benign sensory parasomnia that may nonetheless have significant impact on patients’ quality of life and their perceived well-being. To date, the mechanisms underlying attacks, characterised by a painless perception of abrupt, loud noises at transitional sleep-wake or wake-sleep states, are by and large unclear. Methods and results In order to address the current gap in the knowledge of potential underlying pathophysiology, a retrospective case-control study of polysomnographic recordings of patients presenting to a tertiary sleep disorders clinic with exploding head syndrome was conducted. Interictal (non-attack associated) electroencephalographic biomarkers were investigated by performing macrostructural and event-related dynamic spectral analyses of the whole-night EEG. In patients with exploding head syndrome, additional oscillatory activity was recorded during wakefulness and at sleep/wake periods. This activity differed in its frequency, topography and source from the alpha rhythm that it accompanied. Conclusion Based on these preliminary findings, we hypothesise that at times of sleep-wake transition in patients with exploding head syndrome, aberrant attentional processing may lead to amplification and modulation of external sensory stimuli.
The Long-Term Effect of Smoking on 10 Years’ Survival and Success of Dental Implants: A Prospective Analysis of 453 Implants in a Non-University Setting

Background: The purpose of this study was to compare the survival and peri-implant bone loss of implants with a fluoride-modified surface in smokers and non-smokers. Material and Methods: All patients referred for implant treatment between November 2004 and 2007 were scrutinized. All implants were placed by the same surgeon (B.C.). The single inclusion criterion was a follow-up time of at least 10 years. Implant survival, health, and bone loss were evaluated by an external calibrated examiner (S.W.) during recall visits. Radiographs taken at recall visits were compared with the post-surgical ones. Implant success was based on two arbitrarily chosen success criteria for bone loss (≤1 mm and ≤2 mm bone loss after 10 years). Implant survival in smokers and non-smokers was compared using the log-rank test. Both non-parametric tests and fixed model analysis were used to assess bone loss in both groups. Results: A total of 453 implants in 121 patients were included for survival analysis, and 397 implants in 121 patients were included for peri-implant bone-loss analysis. After a mean follow-up time of 11.38 years (SD 0.78; range 10.00–13.65), 33 implants out of 453 initially placed had failed in 21 patients, giving an overall survival rate of 92.7% and 82.6% on the implant and patient level, respectively. Cumulative 10 years’ survival rate was 81% on the patient level and 91% on the implant level. The hazard of implant loss in the maxilla was 5.64 times higher in smokers compared to non-smokers (p = 0.003). The hazard of implant loss for implants of non-smokers was 2.92 times higher in the mandible compared to the maxilla (p = 0.01). The overall mean bone loss was 0.97 mm (SD 1.79, range 0–17) at the implant level and 0.90 mm (SD 1.39, range 0–7.85) at the patient level. Smokers lost significantly more bone compared to non-smokers in the maxilla (p = 0.024) but not in the mandible. Only the maxilla showed a significant difference in the probability of implant success between smokers and non-smokers (≤1 mm criterion p = 0.003, ≤2 mm criterion p = 0.007). Taking jaw into account, implants in smokers experienced a 2.6 higher risk of developing peri-implantitis compared to non-smokers (p = 0.053). Conclusion: Dental implants with a fluoride-modified surface provided a high 10 years’ survival with limited bone loss. Smokers were, however, more prone to peri-implant bone loss and experienced a higher rate of implant failure, especially in the upper jaw. The overall bone loss over time was significantly higher in smoking patients, which might be suggestive for a higher peri-implantitis risk. Hence, smoking cessation should be advised and maintained after implant placement from the perspective of peri-implant disease prevention.
Synergistic Tribo-Activity of Nanohybrids of Zirconia/Cerium-Doped Zirconia Nanoparticles with Nano Lamellar Reduced Graphene Oxide and Molybdenum Disulfide

Zirconia and 10%, 20%, and 30% cerium-doped zirconia nanoparticles (ZCO), ZCO-1, ZCO-2, and ZCO-3, respectively, were prepared using auto-combustion method. Binary nanohybrids, ZrO2@rGO and ZCO-2@rGO (rGO = reduced graphene oxide), and ternary nanohybrids, ZrO2@rGO@MoS2 and ZCO-2@rGO@MoS2, have been prepared with an anticipation of a fruitful synergic effect of rGO, MoS2, and cerium-doped zirconia on the tribo-activity. Tribo-activity of these additives in paraffin oil (PO) has been assessed by a four-ball lubricant tester at the optimized concentration, 0.125% w/v. The tribo-performance follows the order: ZCO-2@rGO@MoS2 > ZrO2@rGO@MoS2 > ZCO-2@rGO > ZrO2@rGO > MoS2 > ZrO2 > rGO > PO. The nanoparticles acting as spacers control restacking of the nanosheets provided structural augmentation while nanosheets, in turn, prevent agglomeration of the nanoparticles. Doped nanoparticles upgraded the activity by forming defects. Thus, the results acknowledge the synergic effect of cerium-doped zirconia and lamellar nanosheets of rGO and MoS2. There is noncovalent interaction among all the individuals. Analysis of the morphological features of wear-track carried out by scanning electron microscopy (SEM) and atomic force microscopy (AFM) in PO and its formulations with various additives is consistent with the above sequence. The energy dispersive X-ray (EDX) spectrum of ZCO-2@rGO@MoS2 indicates the existence of zirconium, cerium, molybdenum, and sulfur on the wear-track, confirming, thereby, the active role played by these elements during tribofilm formation. The X-ray photoelectron spectroscopy (XPS) studies of worn surface reveal that the tribofilm is made up of rGO, zirconia, ceria, and MoS2 along with Fe2O3, MoO3, and SO42− as the outcome of the tribo-chemical reaction.
Setup of an Extraction Method for the Analysis of Carotenoids in Microgreens

Microgreens are gaining increasing interest as a potential functional food due to their relevant contents of micronutrients and bioactive compounds, including carotenoids. Nevertheless, the analysis of carotenoids is inherently difficult, due to their thermal and chemical susceptibility, as well as to their varying polarity. From this point of view, extraction is the most critical step, compared to chromatographic separation and detection. Thus, the reliability of data on carotenoids should be guaranteed by a constant focus on analytical issues, with appropriate adaptations to each sample matrix. In this research, a specific extraction procedure for the analysis of carotenoids in microgreens was developed. Solvent composition, extraction time, solvent/sample ratio, and repeated extractions were evaluated. The obtained protocol showed recovery of 97.2%, limits of quantitation of 5.2 μg·g−1 for lutein and 15.9 μg·g−1 for β-carotene, as well as intra-day mean repeatability of 5.7% and inter-day mean repeatability of 4.7%.