Miracle-dz/UniFAR-FTUs huggingface dataset:
ENDOCARDITIS PROPHYLAXIS IN DENTAL PRACTICE: EVALUATION OF KNOWLEDGE AMONG DENTISTS, AND CARDIOLOGISTS

Background: Infective endocarditis (IE) is a rare condition that is associated with considerable morbidity and mortality. Almost 100 years ago, the links between endocarditis and procedures, particularly dental procedures, were postulated. Over 50 years ago the first guidelines recommending antibiotic prophylaxis (AP), with the aim of preventing IE from developing after dental procedures, were proposed. Objective: This study aimed to assess the degree of knowledge about endocarditis prophylaxis (EP) among cardiologists, and dentists, and to identify the areas of knowledge that require attention Methods: We conducted a cross-sectional study of 43 cardiologists and 87 dentists in the city of Rabat. Respondents completed a questionnaire to evaluate their knowledge of EP after signing their informed consent. Data were examined through analysis of variance using the chi-squared test (XÂ²) and Fishers exact test to test the significance of the differences between proportions. Findings: 53.5% of cardiologists report following the European Society of Cardiology (ESC) against 62.1% of dentists refer to the French Agency for Health Product Safety (FAHPS), 27.9% of cardiologists are aware of cardiac conditions with a high risk of IE compared to 75.9% of dentists. 2.3% of cardiologists are aware of invasive oral procedures against 54% for dentists. 69% of cardiologists and 70% of dentists have a correct antibiotic prophylaxis prescription regime. 4.7% of cardiologists and 24.1% of dentists know the meaning of spontaneous bacteremia. Conclusion : Both groups had inadequate knowledge of dental procedures. Dentists showed a greater knowledge of heart disease requiring prophylaxis in dental practice. It is thus necessary to reinforce EP knowledge in undergraduate and postgraduate programs and to encourage dentists and cardiologists to keep up-to-date on this issue.
The simulation of plasma in magnetic conical-cusp mirrors using COMSOL multiphysics

In nuclear fusion plasma, open magnetic systems have advantages, including high beta, no neoclassical radial transport, ease preservation, and upgrades. Magnetic Conical-Cusp Mirror is one of these systems that has attracted the attention of researchers. In the Conical-Cusp Mirror device, plasma is confined by various magnetic coils with different current directions. In this work, a Conical-Cusp Mirror plasma system and a simple magnetic mirror plasma were simulated by COMSOL Multiphysics. Moreover, magnetic field gradient and plasma beta were compared in these two systems. The results showed that the Conical-Cusp Mirror plasma is more stable and has higher beta.
The Impacts of Wildfires on Ozone Production and Boundary Layer Dynamics in California's Central Valley

Abstract. We investigate the role of wildfire smoke on ozone photochemical production (P(O3)) and atmospheric boundary layer (ABL) dynamics in California's Central Valley during June–September from 2016 to 2020. Wildfire events are identified by the Hazard Mapping System (HMS) and the Hybrid Single Particle Lagrangian Integrated Trajectory Model (HYSPLIT). Air quality and meteorological data are analyzed from 10 monitoring sites operated by the California Air Resources Board (CARB) across the Central Valley. On average, wildfires were found to influence air quality in the Central Valley on about 20 % of the total summer days of the study. During wildfire-influenced periods, maximum daily 8 h averaged (MDA8) O3 was enhanced by about 5.5 ppb or 10 % of the median MDA8 (once corrected for the slightly warmer temperatures) over the entire valley. Overall, nearly half of the total exceedances of the National Ambient Air Quality Standards (NAAQS) where MDA8 O3 > 70 ppb occur under the influence of wildfires, and approximately 10 % of those were in exceedance by 5 ppb or less indicating circumstances that would have been in compliance with the NAAQS were it not for wildfire emissions. The photochemical ozone production rate calculated from the modified Leighton relationship was also found to be higher by 50 % on average compared with non-fire periods despite the average diminution of j(NO2) by ∼ 7 % due to the shading effect of the wildfire smoke plumes. Surface heat flux measurements from two AmeriFlux sites in the northern San Joaquin Valley show midday surface buoyancy fluxes decrease by 30 % on average when influenced by wildfire smoke. Similarly, afternoon peak ABL heights measured from a radio acoustic sounding system (RASS) located in Visalia in the southern San Joaquin Valley were found to decrease on average by 80 m (∼ 15 %) with a concomitant reduction of downwelling shortwave radiation of 54 Wm−2, consistent with past observations of the dependence of boundary layer heights on insolation.
Computer-Aided Prediction and Identification of Phytochemicals as Potential Drug Candidates against MERS-CoV

The Middle East respiratory syndrome coronavirus (MERS-CoV) is the major leading cause of respiratory infections listed as blueprint of diseases by the World Health Organization. It needs immediate research in the developing countries including Saudi Arabia, South Korea, and China. Still no vaccine has been developed against MERS-CoV; therefore, an effective strategy is required to overcome the devastating outcomes of MERS. Computer-aided drug design is the effective method to find out potency of natural phytochemicals as inhibitors of MERS-CoV. In the current study, the molecular docking approach was employed to target receptor binding of CoV. A total of 150 phytochemicals were docked as ligands in this study and found that some of the phytochemicals successfully inhibited the catalytic triad of MERS-CoV. The docking results brought novel scaffolds which showed strong ligand interactions with Arg178, Arg339, His311, His230, Lys146, and Arg139 residues of the viral domains. From the top ten ligands found in this study (i.e., rosavin, betaxanthin, quercetin, citromitin, pluviatilol, digitogenin, ichangin, methyl deacetylnomilinate, kobusinol A, and cyclocalamin) based on best S -score values, two phytochemicals (i.e., pluviatilol and kobusinol A) exhibited all drug-likeness properties following the pharmacokinetic parameters which are important for bioavailability of drug-like compounds, and hence, they can serve as potential drug candidates to stop the viral load. The study revealed that these phytochemicals would serve as strong potential inhibitors and a starting point for the development of vaccines and proteases against MERS-CoV. Further, in vivo studies are needed to confirm the efficacy of these potential drug candidates.
Investment and Margin Risk Analysis of Robusta Coffee Futures Contract at Jakarta Futures Exchange

Futures trading is developing rapidly in various countries and has become one of the supports for economic growth. However, studies on investment in futures contracts in Indonesia, particularly in measuring risk are still limited. This study aims to calculate the maximum potential loss on investment and the estimated margin on robusta coffee futures at JFX using Value at Risk (VaR). The analysis used symmetrical and asymmetric GARCH (Exponential-GARCH, Threshold-GARCH, and GJR-GARCH). It used data of robusta coffee price, covering spot prices, March contract prices, and September contract prices for the 2016-2019 period. The result of the study indicates that the GARCH (1,1) is the most suitable model for the three robusta coffee prices. Based on the VaR value, the investment risk in the robusta spot is higher than the robusta contract. The margin value interval that may be applied to JFX robusta coffee based on spot price analysis, March contracts, and September contracts reach 2.39%-2.91%.
The thermoelectric performance of anisotropic SnSe doped with Na

Lead-free polycrystalline SnSe is a promising thermoelectric compound consisting of earth-abundant elements. However, the poor electrical transport property for low intrinsic defect concentration (3 × 1017 cm−3) limits the usage of the stoichiometric SnSe compound. In this work, Na2Se as an acceptor was doped into SnSe in order to optimize the electrical transport properties, especially to increase the carrier concentration. As a result, the carrier concentrations increased and saturated at about 1.0 × 1019 cm−3 for Na0.01Sn0. 99Se at 300 K, and a maximum power factor of 0.48 mW m−1 K−2 was obtained. A maximum zT value of 0.75 was obtained at 823 K for Na0.01Sn0. 99Se along the direction perpendicular to the sintering pressure, which is 25% higher than that (0.6) of the undoped SnSe compound.
Characterization of industrial discarded novel Cymbopogon flexuosus stem fiber: A potential replacement for synthetic fiber

In this research article, a leftover of Cymbopogon flexuosus stem (CFS) collected from the oil extraction industry was examined for its ability as a reinforcing agent in a polymer composite. Anatomical, morphological, physical, chemical, mechanical, and thermal characteristics of the CFS ﬁber were examined. Chemical analysis revealed the presence of higher amount of cellulose (68.13%), which offers better bonding properties and higher tensile strength (431.19 ± 23.96 MPa). Moreover, the density of the fiber (1270 kg/m3) found using physical analysis was less than that of synthetic fibers, which paves a path in replacing hazardous synthetic fiber. Solid-state nuclear magnetic resonance and Fourier transform infrared spectrum spectroscopy analyses were conducted to study the functional groups of the extracted CFS fiber. The thermal stability (253.17°C), activation energy (73.01 kJ/mol), and maximum degradation temperature (345.08°C) were investigated by thermogravimetric analysis. X-ray diffraction analysis confirmed the semi-crystalline nature of the fiber with crystallinity index (46.02%) and crystallite size (13.96 nm). The CFS had a smooth surface, as conformed by an atomic force microscopy and scanning electron microscope analysis. Altogether, this study highlights the feasibility of leftover CFS fiber residue as reinforcement in biopolymer matrices replacing synthetic fiber.
Ab Initio Study of Structural, Electronic, and Hyperfine Properties of n-type SnO2:Ta Semiconductor

: A detailed theoretical ﬁ rst-principles study of structural, electronic, and hyper ﬁ ne properties at Sn and Ta sites of undoped and Ta-doped rutile SnO 2 is presented, using the Full-Potential Augmented Plane Wave plus local orbitals (FP-APW+lo) method. In the Ta-doped systems, we performed calculations for two di ﬀ erent charge states. The predicted electric-ﬁ eld-gradient (EFG) tensor, the key magnitude in this study, for both charge states of the impurity result to be almost equal and in good agreement with Time-Di ﬀ erential Perturbed γ − γ Angular Correlation (TDPAC) results in 181 Ta-doped SnO 2 thin ﬁ lms. This study enables at present to discuss the origin of the EFG and the role played by the structural anisotropic contractions introduced by the Ta atom and the impurity charge state on the hyper ﬁ ne properties. To determine the correct charge state of the impurity, we performed energetic studies, predicting the metallic behavior of degenerate semiconductors, in agreement with resistivity experimental results obtained in samples with the same Ta dilution.
Synthesis and study of zinc oxide nanorods for semiconductor adsorption gas sensors

Gas-sensitive coatings based on zinc oxide nanorods were synthesized by a low-temperature hydrothermal method. It was shown that the synthesis of nanorods significantly increases the sensitivity of the samples to isopropyl alcohol vapors. Zinc oxide nanorods are promising for practical application in semiconductor adsorption gas sensors.
The effect of problem based learning oriented by lesson study with adobe flash on critical thinking skill

This study is aimed to determine the improvement of critical thinking skill using problem based learning oriented by lesson study with adobe flash compared to using direct instruction. A quasi-experimental design was employed for the study. The sample was selected purposive sampling technique. The experimental group was taught using problem based learning oriented by lesson study with adobe flash whiles the control group was taught using direct instruction. The data was collected using a critical thinking skill test consist of 20 multiple choices and statistically analyzed using SPSS software. The results showed that the improvement of critical thinking skill using problem based learning oriented by lesson study with adobe flash is better than using direct instruction.
Interconnected PVDF-CTFE hydrophobic membranes for MD desalination: effect of PEGs on phase inversion process

In this work, poly(vinylidene fluoride-co-chlorotrifluoroethylene) (PVDF-CTFE) was used for hydrophobic membrane preparation by the non-solvent induced phase inversion (NIPS) technique. The effects of poly(ethylene glycol) (PEG) molecular weight and dosage were investigated in terms of the membrane morphology, contact angle, surface free energy, and membrane pore structure for both surface pores and overall pores. All membranes possessed a typical liquid–liquid demixing asymmetric structure and the contact angles were higher than 85°. Furthermore, increasing the PEG molecular weight and dosage significantly altered the membrane pore structure and surface roughness as a result of the variation of the phase inversion process. The solid–liquid demixing was responsible for the variation of membrane morphology, pore structure, hydrophobicity, and DCMD performance as PEGs with higher molecular weight or dosage were added. The PVDF-CTFE membranes were suitable for MD application owing to their high hydrophobicity, small pore size with narrow pore distribution, high DCMD performance, especially the interconnected pore structure. The membrane containing 5 wt% PEG-400 was evidenced to be the optimal one for the MD process, mainly according to the high interconnected pore structure which provide more passages for vapour transfer. The permeate flux was 17.98 kg (m−2 h−1) with a conductivity as low as 7 μS cm−1 at the temperature difference of 30 °C. In addition, an excellent performance sustainability was observed including a relatively steady permeate flux and conductivity during the 360 h continuous DCMD operation.
Influence of Tobiko-Mixed Artificial Diet on Textile Properties of Bombyx mori Silkworm Cocoons

ABSTRACT We attempted to use tobiko powder, a byproduct of the konjac cake production, to rear the 5th-instar silkworms by mixing it in the artificial diet, and found that tobiko powder was usable up to the mixing ratio of 20 wt%. Even when the content of mulberry leaf powder in the diet was decreased down to 10 wt% with inversely increasing the tobiko powder up to 20 wt%, the 5th-instar silkworms yielded cocoons comparable to the conventional rearing. However, the spinning habit of the silkworm was a little modified probably by the bioactive chemicals contained in the tobiko powder. Further, yellowing occurred on the surface of the trial raw silk fibers, suggesting that some substances contained in the tobiko powder were excreted in the sericin layer of the cocoon threads. Such change in the composition of sericin layer effectively promoted the enzymatically degumming and then, a glossiness of the degummed fibers was enhanced due to the formation of the fibrillary lines passing along the fiber axis on the fiber surface. In addition, WAXD analysis revealed that the crystallinity of the trial fibers was a little superior to that of the conventional fibers.
Research on vehicle cruise control based on online asynchronous supervised reinforcement learning

This paper proposes a vehicle cruise control strategy based on asynchronous supervised reinforcement learning, which improves the driver’s reception in the process of vehicle deceleration and following. The control strategy takes actor-critic network as the basic control unit, which guides the control strategy to achieve driver-likely cruise effect by adding real driver cruising data into the supervision network. Simultaneously, combined with the driver online feedback mechanism for real-time training, it realizes offline training and online updating of network parameters. The simulation results show that the asynchronous supervised reinforcement learning algorithm can quickly update the parameters of the control network, and constantly update the control strategy by online learning combined with the actual driving data to better simulate the driver’s driving characteristics.
Single-index Thresholding in Quantile Regression

Abstract Threshold regression models are useful for identifying subgroups with heterogeneous parameters. The conventional threshold regression models split the sample based on a single and observed threshold variable, which enforces the threshold point to be equal for all subgroups of the population. In this article, we consider a more flexible single-index threshold model in the quantile regression setup, in which the sample is split based on a linear combination of predictors. We propose a new estimator by smoothing the indicator function in thresholding, which enables Gaussian approximation for statistical inference and allows characterizing the limiting distribution when the quantile process is interested. We further construct a mixed-bootstrap inference method with faster computation and a procedure for testing the constancy of the threshold parameters across quantiles. Finally, we demonstrate the value of the proposed methods via simulation studies, as well as through the application to an executive compensation data.
Identification of Phishing Urls Using Machine Learning

Phishing is a typical assault on unsuspecting individuals by making them to reveal their one-of-a-kind data utilizing fake sites. The target of phishing site URLs is to purloin the individual data like client name, passwords and web based financial exchanges. Phishers utilize the sites which are outwardly and semantically like those genuine sites. As innovation keeps on developing, phishing strategies began to advance quickly and this should be forestalled by utilizing against phishing systems to recognize phishing. AI is a useful asset used to endeavor against phishing assaults. We as a whole know bunches of assaults are happening continuously situation in light of phishing URLS. There is no programmed procedure has been set up so far Multiple assaults of phishing URLs has not yet coordinated. In the proposed framework finding the phishing assaults/URLs, the System will identify various phishing assaults in equal succession and caution the ordinary clients with respect to phishing URLs.
Incidental Exposure and News Engagement: Testing Temporal Order and the Role of Political Interest

Abstract In the contemporary media environment, and particularly on social media platforms, people are embedded in multiple, intersecting flows of political information generated by a wide range of curating actors, and two sets of predictions have emerged in the literature to explain these dynamics of political information exposure and engagement. Theory on incidental exposure suggests that it will lead to news engagement, particularly among the least politically interested individuals. Meanwhile, research on news algorithms suggests the reverse temporal ordering and an antecedent role for political interest. The goals of this study are to (a) theoretically integrate these claims into the ‘curated flows’ framework, (b) to test orthogonal predictions about temporal ordering and the role of political interest, and (c) to compare models by testing cross-lagged relationships between incidental exposure and news sharing. Analysing a two-wave online survey of adult internet users in the United States, results show support for both sets of predictions; however, results also show key differences in the role played by political interest. Results are discussed in light of their implications for theory about news exposure and engagement in the contemporary media environment.
Lung region extraction from CT images of diffuse lung disease cases by deep learning

Diffuse lung diseases (DLD) are widely distributed in lungs. Because the opacity patterns of DLD on CT images are complex and various, the diagnostic results may be different between doctors depending on their experience and subjective decision on them. In order to solve this problem, performing image analysis using CAD (Computer-Aided Diagnosis) systems attracts attention. To achieve high performance in diagnosis by using these CAD systems, it is necessary to first perform lung region extraction as preprocessing for limiting the target domain. However, by using the existing systems, it is difficult to extract lung regions from all five typical shadow patterns of DLD and normal lungs. In this study, we aimed to extract lung regions from CT slices containing DLD shadows using the U-net for improving the CAD performance.
Faraday effect in cubic crystals

Question de la validite de la loi d'addivite de l'effet Faraday dans des cristaux cubiques. Types de variations de cet effet observes dans des cristaux comprenant des transitions de phase du second ordre. Determination de l'effet Faraday specifique de 176 cristaux cubiques et de 16 cristaux non cubiques de composition chimique differente. Evaluation de la dependance de cet effet avec la temperature (220-310 K). Anomalies pour les cristaux ayant des transitions de phase dans le domaine de temperatures
Motivators for Cannabis Use Among Young Adults in Outpatient Psychiatric Care: A Qualitative Study

Cannabis use is prevalent among youth with mental illness, despite the increased risk of exacerbating psychiatric symptoms. The rapidly changing legality of cannabis has contributed to its normalization and decreased perceived risks. This study qualitatively gathered young adult psychiatric patients’ (n=15) perspectives on cannabis to inform a use reduction intervention. NVivo12 was used to organize coded data and facilitate analysis. Motivations to use included viewing cannabis utilization as normalized, supported, and a safer alternative to psychiatric medications. Facilitators for decreasing use were cannabis’ inadequacy at long-term symptom relief, the negative psychiatric sequelae seen in other users, and moderation of intake. Recommendations for the intervention included avoiding overly critical content and providing behavioral skills to aid reduction while improving psychiatric symptoms. Young adults in psychiatric care have unique motivations for cannabis consumption and decreasing use, which should be targeted in future interventions.
COVID-19, frontline hotel employees’ perceived job insecurity and emotional exhaustion: Does trade union support matter?

Abstract Under the lens of conservation of resources and social exchange theories and job demands-resources model, this research aimed at advancing the knowledge regarding the role of trade union support (TUS) in tempering the impact of perceived health risk of COVID-19 (PHRCV19) on frontline hotel employees (FHEs)’ job insecurity and emotional exhaustion (EE), a research topic that is thus far overlooked. An explanatory sequential mixed-method design was adopted. Quantitative data collected through a two-wave survey from 291 FHEs were performed to test the hypotheses using SmartPLS, and 16 in-depth interviews were then analyzed to gain a deeper understanding of the quantitative study’s findings and identify the right ways to enhance employee resilience during COVID-19. We found that (1) TUS directly reduces perceived job insecurity (PJI), (2) PHRCV19 has a positive effect on PJI and EE, and (3) PJI positively influences EE; at the same time, PJI partially mediates the PHRCV19–EE relationship. However, the moderating role of TUS on the impact of PHRCV19 on PJI, and that of PJI on EE, is insignificant. This research also provided practical implications helping reduce FHEs’ PJI and EE.