Miracle-dz/UniFAR-FTUs huggingface dataset:
Effect of the COVID-19 Pandemic on Contact Lens Wear in Greece

Purpose: This study demonstrates the actions that took over the contact lens (CL) wearers in Greece after the COVID-19 pandemic. Methods: The study includes nameless web-based survey used to measure participants demographics, CL wear history, and custom wear activity of CL in a stage of noticeable risk of infection due to CL wear during the COVID-19 pandemic. Results: During the lockdown A’ in Greece about half of the participants (42.5%) believe that the perception risk of infection using CL was extremely effective (29%) and very effective (13.5%). Only a minority (18 %) of the participants do believe that the use of CL increases the risk of COVID-19 infection. Another population (43%) do not agree with this opinion and more than a third of them (39%) resemble that are not affected by this opinion or are less informed. Conclusion: This study presents the likelihood of reducing or ceasing the use of CLs during the Original Research Article Chandrinos and Tzamouranis; OR, 14(1): 22-29, 2021; Article no.OR. 63054 23 COVID-19 pandemic lockdown and a relationship between the perceived risk of infection and CL use. There was also a predisposition to alter the frequency of CL wear. All eye care practitioners should give more advice to their patients that continue to wear CL and assist them to act in accordance with the new rules of handling and in favour of occasional CL wear.
A novel approach to tool condition monitoring based on multi-sensor data fusion imaging and an attention mechanism

Tool wear does great damage to product quality and machining efficiency. In this paper, a new tool condition monitoring (TCM) method based on a multi-sensor data fusion imaging and attention mechanism is proposed to indirectly measure and monitor tool wear. First, the multi-sensor signals collected during the operation of the machine tool are encoded and fused. A novel triangular matrix of angle summation method is proposed to fuse multi-sensor time-series signals at the data layer and to image them as two-dimensional images. The method used here effectively retains the detailed characteristics of the data, and also effectively retains the internal time relationship of the signal. In addition, a deep residual network with a convolution block attention module is used to extract the deep features from the encoded image and identify the wear stage of the tool. The proposed deep-learning network is then applied to TCM. It selects information in the channel and spatial domains based on its attention mechanism, and increases network depth by combining residual blocks to realize deep feature extraction. Compared with traditional machine learning methods, this end-to-end deep learning model does not rely on feature engineering, which requires a lot of expert knowledge and artificial experience. In our experimental study, a public data set was used to train the model, and the results showed that the accuracy of the model proposed in this paper was as high as 94%. To further verify its feasibility and effectiveness, the proposed model was also compared with other methods.
College student’s social anxiety: a study of the young people mental health in digital age

Purpose of this study is to analyze whether in the current era social anxiety problems are still developing among college students and whether there are any differences in the level of social anxiety was based on the year of entry (new college students - old college students) and gender. This research is a quantitative-descriptive and comparative studies. Hypotheses are there is no difference in social anxiety level based on the year of entry nor gender. The subjects are undergraduate college students totaled 364 people. Instrument used for data collection is Liebowitz Social Anxiety Scale-Self Report (LSAs-SR). Results showed that 76.9% of the subjects experienced social anxiety. There is no difference in the level of social anxiety among new college students and old college college students nor between male college students and college students.
A Resource-Constrained and Privacy-Preserving Edge-Computing-Enabled Clinical Decision System: A Federated Reinforcement Learning Approach

Internet-of-Things-enabled E-health system, which could monitor and collect the personal health information (PHI), has gradually transformed the clinical treatment to a more personalized way with in-home monitoring smart devices. Then, with the collected PHI, clinical decision support systems (CDSSs), which are based on data mining techniques and historical electronic medical records (EMRs) to help clinicians make proper treatment decisions, have attracted considerable attention. To address issues, such as network congestion and low rate of responsiveness for traditional methods when implementing CDSSs, we integrate the technologies mobile-edge computing (MEC) and software-defined networking for exploiting the computation resources and storage capacities among edge nodes (ENs) (i.e., MEC servers) in our model. Based on this integrated system, each edge node will deploy a double deep $Q$ -network (DDQN) to obtain a stable and sequential clinical treatment policy. It is enabled by a novel fully decentralized federated framework (FDFF) for aggregating models of DDQN and extracting the knowledge from EMRs across all ENs. Furthermore, we discuss the convergence of FDFF in resource-constrained environments. However, since most EMRs are faced with stringent privacy concerns, we adopt two additively homomorphic encryption schemes to prevent leakage of EMRs’ privacy during the training process of FDFF. Finally, we measure the time cost of our additively homomorphic encryption schemes and validate DDQN with experiments on large data sets based on FDFF, which shows promising performance on clinician treatment.
A Double-blind, Placebo-controlled, Randomized, Longitudinal Study on the Effects of a Plant-based Dietary Supplement on Nitric Oxide and Mitochondrial Metabolic Activity

During the past two decades, metabolic dysfunction and concomitant reduction-oxidation reaction (redox) imbalances (i.e., oxidative stress) have been suggested to be associated with numerous age-related chronic diseases. One profound result of metabolic imbalances is endothelial dysfunction, a pathophysiological condition that increases risk of downstream chronic disease consequences. Healthy endothelial function has been positively associated with elevated levels of circulating nitric oxide (NO). Consequently, a natural, plant-based material that may safely increase endogenous NO levels, reduce redox imbalance, and promote improved metabolic response could be of significant interest and benefit. In this first study of its kind, we conducted a longitudinal, randomized, double-blind, placebo-controlled study of S7, a proprietary polyphenol-rich fruit, vegetable, and herb-based material previously reported to reduce reactive oxygen species (ROS) and to increase NO. Specifically, we measured changes in real-time cellular generation of ROS and changes in levels of bioavailable NO (measured as circulating NOHb) in 42 overweight or slightly obese individuals who were recruited into one of three groups: placebo, 25mg of S7, and 50mg of S7. Results suggest that after 90 days of once-daily supplementation, the 25mg and 50mg S7 groups exhibited diminished mitochondrial ROS generation (~54% and ~75%, respectively) compared to placebo, which exhibited a slight increase (>12%) (p = 0.049). Furthermore, circulating NOHb levels significantly increased in the 25mg and 50mg S7 groups (33.87% and 53.43%, respectively) compared to placebo (p < 0.001). Together, these results suggest that long-term daily supplementation of S7 may provide potential benefits related to healthy endothelial function and reduced mitochondrial dysfunction.
Gender difference in extreme cardiac remodelling in endurance olympic athletes assessed by non-contrast CMR

Type of funding sources: None. Male and female athletes present difference spectrum of cardiac remodelling related to their sport activity. However data in elite female athletes are scarce and mainly limited to echocardiography evaluation. The aim of the study was to assess gender difference in extreme cardiac remodelling in Olympic athletes engaged in endurance sport assessed by non-contrast Cardiovascular Magnetic Resonance including Mapping. Methods Olympic athletes engaged in endurance sport (rowing, canoeing, mid/long distance swimming) were examined with history, physical examination, 12-lead and exercise electrocardiogram, and echocardiography as part of their evaluation prior the Olympic games (Tokyo 2020). Athletes with unremarkable evaluation were undergone to non-contrast CMR including Mapping. The following parameters were calculated: indexed left ventricle (LV) and right ventricle (RV) end-diastolic (EDVi) and end-systolic volumes (ESVi), stroke volume (SVi), ejection fraction (EF), left and right atria area (LAAi and RAAi), LV Mass (Massi) and maximum wall thickness (MWT), RV/LV EDV ratio, spericity index [SI=(long axis diameter/2)3 * 4,187], myocardial native T1 (nT1) and T2 Mapping. 51 caucasian elite athletes (without difference in term of age, years of training and hours of training/week) were enrolled and 59% were male. Male showed greater LV EDVi (123 ± 28 ml vs 103 ± 10, p = 0.003), ESVi (55 ± 14 ml vs 44 ± 7, p = 0.001), SVi (68 ± 15 ml vs 59 ± 7, p = 0.023), Massi (76 ± 19 vs 57 ± 10, p < 0.001), MWT (10 ± 1 mm vs 8 ± 1, p < 0.001) and RV EDVi (129 ± 48 ml vs 104 ± 13, p = 0.026), ESVi (57 ± 10 ml vs 45 ± 9, p < 0.001), SVi (68 ± 15 ml vs 59 ± 7, p = 0.018) compared to female, as expected. LVEF (p = 0.05) and RVEF (p = 0.17) did not show significant difference. Despite greater volumes, SI (43 ± 12% vs 44 ± 8, p = 0.8) and RV/LV EDV ratio (0.99 ± 0.05 vs 1 ± 0.05, p = 0.405) did not differ between male and female athletes, as well as LAAi (13 ± 3 cm2 vs 13 ± 1.5, p = 0.86) and RAAi (13 ± 1.9 vs 13 ± 18, p = 0.56). Native T1 mapping was lower in male compared with female (934 ± 21 ms vs 956 ± 33, p = 0.028) while T2 Map values were slightly higher (53 ± 3.9 ms vs 50 ± 3.8, p = 0.027) . Male endurance Olympic athletes presented higher volumes and LV mass compared to their female counterparts, while atria dimension, systolic function and sphericity index did not differ. Ventricles showed balanced dilatation in both gender. Lower T1 value observed in male suggested cellular hypertrophy. Figure 1 showed CMR images in a male (top row) and a female (bottom row) Olympic athletes: 4 chamber end-diastolic and end-systolic frame and end-diastolic basal short axis (SAX) showed balanced dilatation. Graphs showed higher EDVi and Massi in male compared o female, no difference in sphericity index and lower native T1 mapping. Abstract Figure 1
IMPROVING STUDENTS’ WRITING ABILITY IN DESCRIPTIVE TEXT THROUGH CLUSTERING TECHNIQUE AT TENTH GRADE of MA MA’ARIF ROUDHOTUT THOLIBIN METRO

The objective of this research was to improve the students’ writing ability in descriptive text through clustering technique at the tenth grade of MA Ma’arif Roudhotut Tholibin Metro in academic year 2018/2019. This research was conducted at tenth grade in second semester at MA Ma’arif Roudhotut Tholibin Metro in academic year 2017/2018. The design of this research was classroom action research (CAR). This research was applied collaborative action research, this research was done in two cycle. It is done with; planning, acting, observation and reflecting. In collecting data, the writer uses; test,observation and questionnaire. the application of the clustering technique could improve the students’ writing ability in descriptive text. Based on the results of the observation obtained the students more understanding to make descriptive sentences, and make the descriptive sentences into a descriptive text. The activity make the student become interested to describe the pictures or object, students more active and more anthusiasm in the writing learning process. Then, in Cycle 1 students passed is 15 (60%). In cycle 2 students passes the KKM (80%). Was improved 20% in cycle 2. By this number, the researcher concludes that the minimum target of success, that is 70% of the students in a class, has been achieved in cycle 2, and from the third data we can conclude it was prove that clustering technique can positively improve the students’ writing ability in descriptive text at tenth grade of MA Ma’arif Roudhotut Tholibin Metro in academic year of 2018/2019
Application of Polarization Modulation Infrared Reflection Absorption Spectrosocpy Under Electrochemical Control for Structural Studies of Biomimetic Assemblies

Abstract An ideal bioanalytical method would allow carrying out sensitive, selective, reproducible, fast, and in situ chemical measurements of the composition, structure and function of complex biological systems. Physical chemistry possesses advanced structure analyzing techniques which are suitable to solve, at a sub-molecular level, the structure of biomolecules. However, the prerequisite of the presence of the electrolyte solution limits the number of applicable structure analyzing techniques. Infrared spectroscopy is one of the most powerful analytical techniques used to identify the structure of biomolecules, monitor structural changes under various experimental environments and physical states. In addition, infrared reflection absorption spectroscopy (IRRAS) has been successfully applied to study supramolecular films at the solid|liquid interface. Assemblies of biomolecules belong to a particularly demanding because they bring specific for the maintenance of their functions experimental requirements which have to be taken into account planning in situ spectroelectrochemical experiments. In this paper potnential of in situ IRRAS under electrochemical control for studies of structural changes in assemblies of biomolecules such as lipid bilayers and protein films is described. Studies of different classes of biomolecules bring certain experimetnal conditions concerning the electrolyte composition, pH value, temperature or chemical nature of the solid support, which have to be fulfilled. Obviously, these conditons may significantly restrict the applicability of the in situ PM IRRAS. The selection of the solid substrate with required optical and electrical properties, the optical window and the electrolyte composition have to be adapted to the needs of biomolecules. Adjustement of experimetnal conditions as well as possibilites of the enlargement of the in situ PM IRRAS for studies of biomimetic assemblies is reviewed in this paper. Furthermore, experimetnal resutls reporting potenial driven changes in models of cell membranes and protein films are reviewed. Pioneering studies aiminig at the determination of structural changes in lipid membranes exposed to physiological electric fields and interacting simultaneously with protiens are described.
Factors Influencing International and Domestic Dentists’ Interest in Advanced Periodontal Education

Background: The enrollment of international periodontal students in U.S. dental schools has been increasing in recent years. Interest in applying to a periodontics specialty program may differ between U.S and international dental school graduates. The purpose of this study is to assess, from the perspective of periodontal residents, (1) factors that interest dental students to apply to periodontics programs and (2) differences in background and interest between U.S and international graduates. Methods: A 20-question survey was sent out electronically to periodontics residents. The survey questions were designed to obtain information on the participants’ backgrounds, factors that influenced them to specialize in periodontics, and their preferred features of graduate periodontics programs. The data were analyzed using descriptive statistics for socio-demographic variables, a Wilcoxon two sample test to compare mean Likert scale scores, and Fisher’s exact test for associations between comparison groups. Results: Of the 200 hundred residents invited to participate, 28% responded. The majority of the respondents stated that interest in implantology, previous exposure to periodontal procedures, interest in improving periodontal surgery skills, a good relationship with periodontics faculty, the residency curriculum, advanced program and faculty reputation as influencing factors in selecting periodontics as specialization. The majority of international graduates have up to $50,000 dollars in student debt; by comparison, half of the domestic graduates have a debt of over $250,000 dollars (p ≤ 0.05). Working experience as a dentist was significantly greater among international residents (73%) in comparison to U.S graduates (32%). In contrast with international graduates, U.S graduates more frequent reported that good relationships with the periodontics predoctoral faculty contributed to their interest in periodontics (p ≤ 0.05). Program cost and location had a greater impact on the decision of U.S. graduates than international graduates (p ≤ 0.05). Conclusions: Overall, factors associated with personal finance and predoctoral education have a greater impact on the decision of American graduates than international graduates to pursue an advanced education in periodontics, which may influence the increased enrollment of international students.
Fluid Temperature Detection Based on its Sound with a Deep Learning Approach

: The present study, the main idea of which was based on one of the questions of I.P.T.2018 competition, aimed to develop a high-precision relationship between the fluid temperature and the sound produced when colliding with different surfaces, by creating a data collection tool. In fact, this paper was provided based on a traditional phenomenological project using the well-known deep neural networks, in order to achieve an acceptable accuracy in this project. In order to improve the quality of the paper, the data were analyzed in two ways: I. Using the images of data spectrogram and the known V.G. G.16 network. II. Applying the data audio signal and a convolutional neural network (C.N.N.). Finally, both methods have obtained an acceptable precision above 85%.
Generic Feasibility Assessment: Helping to Choose the Nuclear Piece of the Net Zero Jigsaw

The United Kingdom has declared a climate change policy of 100% reduction in carbon dioxide emissions by 2050. Efforts thus far have been limited solely to electricity generation methods. While progress has been admirable, effort now must be directed at the nation’s non-electrical energy use. Nuclear energy is an essential part of any energy future, since it is low-carbon, firm and supplies synchronous electricity; however the nation’s nuclear strategy to date has been erratic, costly and lacking in strategic oversight. A multitude of reactor designs are on offer for potential uptake, and decision-makers must have clarity of vision on what these systems must deliver before forming a strategy. Choosing between these systems, given the uncharted energy future faced by the UK is a daunting prospect. Generic feasibility assessment offers a tool for decision-makers to assist them in selecting the most suitable nuclear system for chosen future conditions. Generic feasibility assessment offers an alternative to traditional multi-attribute decision analyses, which can be confusing to even committed stakeholders when large numbers of attributes are weighted and compiled. Generic feasibility assessment forms part of a toolkit which will be of utility in achieving net zero by 2050, given the short time that remains.
Inflammatory process as an etiological and prognostic factor of stroke and the goal of potential treatment strategies

Objective. Inflammation is the body’s natural defence mechanism against factors that damage its tissues. However, if it lasts chronically, it may adversely affect the body’s homeostasis. Inflammation is not only a long-known risk factor for the development of atherosclerosis and its complications, but also develops brain tissue damage in the course of ischemic stroke or intracerebral haemorrhage, leading to even greater damage. In addition, the immune system functions are impaired, which increases the risk of infection. Literature review. Drugs that can reduce the risk of stroke by inhibiting vascular damage and modifying the inflammatory process in the central nervous system, including counteracting the risk of infection, have become the subject of many experimental and clinical studies on strokes. Such drugs include canakinumab, human recombinant interleukin-1 receptor antagonist, colchicine, fingolimod, siponimod or natalizumab. Conclusions. Considering all available research results, the therapeutic pathway using anti-inflammatory drugs has a high potential; however, the complications associated with evoked immunosuppression in patients should be kept in mind. The paper presents a review of the literature on the role of the inflammatory process in the pathogenesis of stroke as well as related therapeutic options.
What Key Drivers Are Needed to Implement Material Efficiency Strategies? An Analysis of the Electrical and Electronic Industry in Malaysia and Its Implications to Practitioners

A circular economy can be achieved by the efficient use of materials across different industries and sectors. In the manufacturing sectors, practicing material efficiency is one of the effective strategies to reduce material usage and solid waste generation. However, due to many unknown factors, such as key drivers to enhance material efficiency, most of the time, manufacturers are practicing at the minimum level of material saving. This study aims to examine the key drivers of material efficiency among electrical and electronic (E&E) companies to fulfill the aims of sustainable manufacturing. The data collection and synthesis were conducted using semi-structured interviews and an analytical hierarchy process survey. In this study, thirteen key drivers were found. Five internal drivers and eight external drivers with different priorities were found to influence E&E companies in the practice of material efficiency strategies. In addition, the drivers’ implications to different practitioner groups are suggested. To conclude, achieving material efficiency can be done effectively if the incentivized key drivers are clearly notified. This research is important to show the key drivers that influence the implementation of material efficiency strategies in the E&E industries.
Regulating dielectric performances of Poly(vinylidene fluoride) nanocomposites by individually controlling shell thickness of Core@Double‐Shells structured nanowires

The synthesis of core@double ‐ shells structured TiO 2 @C@SiO 2 nanowires (NWs) with variable thickness of carbon inner shell and SiO 2 outer shell was achieved by individually controlling the chemical vapour deposition time and amount of silicon precursor added in the sol–gel synthesis. The resultant TiO 2 @C@SiO 2 NWs filled nanocomposites exhibited an excellent dielectric performance with simultaneously improved dielectric constant and suppressed dielectric loss, which could be further regulated by individually controlling the carbon inner shell and SiO 2 outer shell thickness. More importantly, the influences of the conductive carbon inner shell and insulated SiO 2 outer shell thickness on the dielectric performance of nanocomposites were clearly revealed. The increase of the conductive carbon inner shell thickness would lead to an increase in dielectric constant and loss of nanocomposites, while the insulated SiO 2 outer shell exhibited a totally opposite law that the dielectric constant and loss of nanocomposites decrease with increasing SiO 2 outer shell thickness. Numerical simulations were also carried out to theoretically verify the relationship between the dielectric loss and SiO 2 outer shell thickness. This promising controllable multi ‐ shell structure could be extended to a variety of hybrids to develop high ‐ performance dielectric nanocomposites.