Miracle-dz/UniFAR-FTUs huggingface dataset:
Management of dental anxiety via distraction technique

Background The purpose of this study was to evaluate the use of a stress ball as a distraction technique on stress levels of patients undergoing a dental procedure. Material and Methods A randomized, split-mouth design was conducted using 20 adult subjects requiring scaling and root planing (Sc/RP) in all four quadrants. Each side of the mouth (maxillary/mandibular) received Sc/RP with local anesthetic with or without the use of a stress-ball distraction over two separate sessions. Subjects completed two pre-procedural questionnaires (Spielberger State-Trait Anxiety Inventory, STAI; Modified Dental Anxiety Scale, MDAS) before and after each treatment session. A Galvanic Skin Response (GSR) sensor (Neulog) was used throughout each session to measure skin conductance or sweat. Results No significant difference in GSR scores was found during treatment with or without the use of the stress ball. Also, no significant differences in the change in STAI or MDAS scores were found with or without the use of a stress ball. Conclusions The results of this study found that the use of a stress ball as a distraction technique did not result in any significant reduction in stress levels in subjects undergoing scaling and root planing with local anesthesia. Key words:Anxiety, distraction, stress ball.
Parent Engagement at a Primarily Latinx High School Campus

ABSTRACT Though there have been multiple studies on engagement among Latinx families, less is known about Latinx parental engagement at the secondary level or about engagement at predominantly Latinx schools. The purpose of this case study was to use Yosso’s concept of community cultural wealth to demonstrate how administrators can engage Latinx parents in an urban high school by being responsive to families’ needs and the ways in which parents want to engage with the school. Our findings have implications for research on parent engagement and for school-based practitioners seeking to engage their communities.
Impact of relative motion of a magnetic field on unsteady magnetohydrodynamic natural convection flow with a constant heat source/sink

This study analyzes time‐dependent magnetohydrodynamics natural convective flow of a viscous incompressible fluid in an annulus with ramped motion of the boundaries. The governing momentum and energy equations are solved analytically, in terms of the modified Bessel function of the first and second kinds. The influence of governing parameters such as the Hartman number, radius ratio, Grashof number, heat absorption parameter, and Prandtl number are discussed with the help of line graphs. It is found that the Hartmann number has a retarding effect on fluid velocity when K = 0.0 and K = 0.5, while the reverse effect is noticed when K = 1.0. The Hartman number also decreases the mass flow rate for all cases of K while it enhances the skin friction at the inner surface of the outer cylinder. It increases the skin friction at the outer surface of the inner cylinder when K = 1.0 and K = 0.0, but decreases the skin friction at the outer surface of the inner cylinder when K = 0.5.
The Impact of “Coal to Gas” Policy on Air Quality: Evidence from Beijing, China

Air pollution has become an increasingly serious environmental problem in China. Especially in winter, the air pollution in northern China becomes even worse due to winter heating. The “coal to gas” policy, which uses natural gas to replace coal in the heating system in winter, was implemented in Beijing in the year 2013. However, the effects of this policy reform have not been examined. Using a panel dataset of 16 districts in Beijing, this paper employs a first difference model to examine the impact of the “coal to gas” policy on air quality. Strong evidence shows that the “coal to gas” policy has significantly improved the air quality in Beijing. On average, the “coal to gas” policy reduced sulfur dioxide (SO2), nitrogen dioxide (NO2), particulate matter smaller than 10 µm (PM10), particulate matter smaller than 2.5 µm (PM2.5) and carbon monoxide (CO) by 12.08%, 4.89%, 13.07%, 11.94% and 11.10% per year, respectively. We find that the “coal to gas” policy is more effective in areas with less energy use efficiency. The finding of this paper suggests that the government should continue to implement the “coal to gas” policy, so as to alleviate the air pollution in Beijing, China.
Döviz Kurlarının Bankacılık Sektörünün Performansı Üzerindeki Etkisi: Türkiye Örneği (2007-2016)

Son donemde yukselen ekonomiler arasinda yer alan Turkiye’nin ekonomik buyumesinin yavasladigi ve para biriminin asiri deger kaybettigi gorulmektedir. Bankacilik sektorunun doviz kurlarindaki oynakliga karsi duyarliliginin yuksek olmasi, sektor performansini ve faaliyetlerini etkilemektedir. Kur ve bankacilik krizleri ile iliskili yapilan analizlerde, kur dalgalanmalari ile bankacilik krizleri arasindaki iliskiye odaklanilmakta ama banka performansi uzerindeki etkiler goz ardi edilmektedir. Bu bakimdan kur hareketlerinin banka performansina etkileri onemli ve uzerinde az durulan bir arastirma konusu olmaktadir. Calismada Turkiye’de doviz kurundaki oynakligin bankacilik sektorunun performansi uzerindeki etkisi incelenecektir. 2007-2016 yillar arasi aylik kur verileri ile net faiz marji, aktif getirisi ve oz kaynak getirisi gibi bankacilik sistemi temelli verileri kapsayan bir orneklem analiz edilmistir. Analizlerde Pesaran ve Shin (1999) ve Pesaran v.d. (2001) onerdigi ARDL modeli kullanilmistir. Ulasilan bulgular; kurlar ile bankacilik sisteminin performansi arasinda uzun donemli bir iliski olmadigini gostermistir. Kur artislarinin bankacilik sektorunun performansini etkilemedigi belirlendiginden, sektorun kur riskine karsi dayanikli oldugu sonucuna varilmistir. Turk bankacilik sektorunun vadeli islem piyasasinda yogunlasmasi, kur riskine duyarliligi olan islemleri kisitlayici duzenlemeler uygulanmasi ve Basel III standartlarina uyum surecinin hizlandirilmasi ile daha saglam bir altyapiya kavusabilecektir.
A New Method for Determining the Degree of Controllability of State Variables for the LQR Problem Using the Duality Theorem

The control performance of a dynamic system can be checked by the degree of controllability. In this work, we present a new method for determining the degree of observability of state variables for the linear quadratic optimal estimation (LQE) problem. We carried out the calculation of the degree of controllability for the linear quadratic optimal control (LQR) problem using a duality theorem. Compared with the traditional measures of controllability such as determinant, trace, and maximal eigenvalue of the inverse controllability Gramian, the proposed degree of controllability was developed for each state variable and takes into account both the controllability Gramian and the cost function. The new method is convenient to apply to LQR problem. In the numerical simulation, we determined the influence of the model parameters on the degree of controllability. Besides that, we analyzed the degree of controllability, which gives an insight into the relationship between the system model design and the control performance.
EVAL Cane: Nonintrusive Monitoring Platform With a Novel Gait-Based User-Identification Scheme

Considering the particularity of fragile people with reduced mobility, we design a nonintrusive platform called EVAL cane to assist and monitor the user’s walking. On the one hand, it has important walking-assistance functions, such as obstacle warning and fall detection. On the other hand, it collects the user’s long-term walking data in the background, which may be the potential physical-health-assessment data. Compared with an ordinary cane, the above two functions are implemented without any burden on the user’s life. In addition, we have considered the authentication security for that the walking data are private. To this end, we propose a novel user-identification scheme, leveraging the user walking gait data collected by EVAL cane. To the best of our knowledge, it is the first time that the gait information collected by cane is used for reinforcing monitoring system security. This scheme does not require the user to remember and enter any identity (such as a password), which is user-friendly for fragile people. In the scheme, a statistics-based rough gait feature-extraction method is put forward at first. Then, in order to improve the identification precision, we design a performance-based feature-deletion (PFD) algorithm to remove the bad features. Finally, a minimum Mahalanobis distance classifier is used. Experimental results show that the user-identification rate without the PFD algorithm can reach as high as 90.48%. In addition, the PFD algorithm further improves the performance by about 6%, reaching an excellent result of 96.43%.
Eroding Trust in Teacher Professionalism: An Ethnomethodological Analysis of Radio Interviews with Czech Experts on Education

Schools and teachers have been subject to a number of debates and often face contradictory demands. In this study we analyse radio interviews with three Czech experts on education. Building on ethnomethodology, namely conversation analysis and membership categorisation analysis, the study was guided by two research questions: (1) What practices and membership categorisation devices do the experts employ when speaking of Czech education and schools? and (2) How do the experts relate to teacher professionalism when characterising Czech education? The analysis shows how the expert's credibility is negotiated, how they problematise gaining fundamental knowledge and skills at schools and situate the learning of "important things" outside school, and how they claim that Czech teachers teach badly while downgrading positive results of Czech schooling. This way the experts cast doubt on basic characteristics of teacher professionalism and thus undermine trust in the professional project in teaching.
Echocardiographic Diagnosis of Postcapillary Pulmonary Hypertension: A RIGHT1 Substudy

Background: Pulmonary hypertension is observed in 70% of patients with left ventricular (LV) dysfunction. Right heart catheterization is the gold standard for a complete evaluation of Pulmonary Hypertension (PH); however, echocardiography represents a powerful initial diagnostic tool. The aim of our study was to evaluate the accuracy of echocardiography for the diagnosis of postcapillary PH, i.e., due to increased left ventricular filling pressures. Methods and Results: We recruited patients with a diagnosis of PH from the RIGHT1 study (Right heart invasive and echocardiographic hemodynamic evaluation in Turin 1). Transthoracic echocardiography was performed within 60 min of cardiac catheterization. High LV filling pressures were defined by a pulmonary arterial wedge pressure (PAWP) greater than 15 mmHg. We assessed numerous morphological and functional features of LV, and their association with PAWP. 128 patients were diagnosed with PH. We observed a significant association between PAWP, the left atrial volume indexed by BSA (LAVi, R2 = 0.27; p < 0.0001) and the E/e’ ratio (R2 = 0.27; p < 0.0001). With these parameters, we implemented a diagnostic algorithm to identify high ventricular filling pressures in PH patients. The application of this algorithm could help identify patients with a diagnosis of postcapillary PH due to high ventricular filling pressures (E/E’ > 15). Conclusions: The echocardiographic parameters with the best association with PAWP in PH patients are E/e’ and LAVi. For these patients, our diagnostic algorithm could improve the diagnostic precision for the definition of subgroups.
Auditory Device Voice Activity Detection Based on Statistical Likelihood-Ratio Order Statistics

This paper proposes a technique for improving statistical-model-based voice activity detection (VAD) in noisy environments to be applied in an auditory hearing aid. The proposed method is implemented for a uniform polyphase discrete Fourier transform filter bank satisfying an auditory device time latency of 8 ms. The proposed VAD technique provides an online unified framework to overcome the frequent false rejection of the statistical-model-based likelihood-ratio test (LRT) in noisy environments. The method is based on the observation that the sparseness of speech and background noise cause high false-rejection error rates in statistical LRT-based VAD—the false rejection rate increases as the sparseness increases. We demonstrate that the false-rejection error rate can be reduced by incorporating likelihood-ratio order statistics into a conventional LRT VAD. We confirm experimentally that the proposed method relatively reduces the average detection error rate by 15.8% compared to a conventional VAD with only minimal change in the false acceptance probability for three different noise conditions whose signal-to-noise ratio ranges from 0 to 20 dB.
A Curve Free Method based on Bayesian Optimization for Oncology Phase I Clinical Trials

The main goal of oncology phase I clinical trials is to identify a maximum tolerated dose. Although many authors have offered a variety of methods for the maximum tolerated dose, conventional methods have some potential shortcomings. Parametric model-based methods may provide incorrect results due to model misspecification because not only little is known about dose--toxicity relationship but also the sample size is small. In addition, most methods ignore uncertainty of estimated dose--toxicity relationship in their dose selection process. To address these concerns, we propose a Bayesian optimization design for estimating the maximum tolerated dose. Our proposed method utilizes a Bayesian optimization framework, so that a distribution of the dose--toxicity relationship is nonparametrically estimated and the dose is selected by balanced information between exploration and exploitation to avoid concentrating on a local optimum during a trial. Therefore, our proposed method corresponds to the model specification issue through utilizing a nonparametric model and enables us to account for uncertainty during dose selections through treating a distribution of an estimated curve. In this paper, we introduce a Bayesian optimization design under single-agent trials. We compare it with continual reassessment method, modified toxicity probability interval, and a curve-free method based on a product-of-beta prior. Simulation results suggest that our proposed method works successfully in the maximum tolerated dose estimation problem in terms of correct recommendation of a true maximum tolerated dose and it has a potential as being an alternative to existing methods.
Asphalt fatigue endurance limit estimation and impact on perpetual pavement design

ABSTRACT The National Cooperative Highway Research Program (NCHRP) Project 9-38 developed a method for estimating asphalt fatigue endurance limit (FEL) which employs bending beam fatigue (BBF) lives. Another project, NCHRP 9-44A, used BBF test data to formulate a healing-based FEL prediction model. Both procedures were evaluated in this study by utilising data from the National Center for Asphalt Technology Pavement Test Track. The estimated FELs were used in perpetual pavement design to investigate their impact on asphalt thickness. The NCHRP 9-44A-predicted FELs increased with longer rest periods, but largely stabilised after 8 s, which agreed with the NCHRP 9-44A researchers’ conclusion that no healing occurs after a rest period of 5–10 s. Overall, the NCHRP 9-38 method yielded greater FELs. Without binder modification and/or high binder content, both methods provided similar FELs, if a rest period longer than 5 s was entered in the NCHRP 9-44A model. Generally, the NCHRP 9-44A-predicted FELs produced thicker layers. However, for conventional asphalt mixtures, both sets of FEL yielded similar thicknesses, if the NCHRP 9-44A model applied a rest period exceeding 5 s. The NCHRP 9-44A model’s predictive capability will increase if it is recalibrated with mixtures containing modified binder and/or higher binder contents.
Improving executive compensation in the fossil fuel sector to influence green behaviors

The effects of climate change are being felt around the world, and the calls to mitigate are growing louder. In hopes of responding to this call, we examine strategic compensation practices as innovative solutions for tackling climate change. We employ a fixed panel analysis and examine organizational data from an array of global fossil fuel organizations—arguably the principal climate change contributors. Our findings suggest that executive stock-option compensation oriented around a 3-year or more vesting period will enhance organizational green behaviors. The contributions of this study add to the green human resource management literature in offering new perspectives on how compensation practices can enhance green behaviors and clarify key misconceptions related to linking sustainability targets to firm-level compensation schemes.
Advanced steady‐state model for the fate of hydrophobic and volatile compounds in activated sludge

A steady‐state, advanced, general fate model developed to study the fate of organic compounds in primary and activated‐sludge systems. This model considers adsorption, biodegradation from the dissolved and adsorbed phases, bubble volatilization, and surface volatilization as removal mechanisms. A series of modeling experiments was performed to identify the key trends of these removal mechanisms for compounds with a range of molecular properties. With typical municipal wastewater treatment conditions, the results from the modeling experiments show that co‐metabolic and primary utilization mechanisms give very different trends in biodegradation for the compounds tested. For co‐metabolism, the effluent concentration increases when the influent concentration increases, while the effluent concentration remains unchanged when primary utilization occurs, For a highly hydrophobic compound (partition coefficient Kd > 0.01 m3/g VSS), the fraction of compound removed from adsorption onto primary sludge can be very important, and the direct biodegradation of compound sorbed to the activated sludge greatly increases its biodegradation and reduces its discharge with the waste activated sludge. Volatilization from the surface of the primary and secondary systems is important for compounds with moderate to high volatilities (Henry's law constant Hc = 0.001 to 0.1 m3 water/m3 air), especially when these compounds are not biodegradable. Finally, bubble volatilization can be a major removal mechanism for highly volatile compounds (Hc > 0.8 m3 water/m3 air), even when they are highly biodegradable.
Are Water User Associations Prepared for a Second-Generation Modernization? The Case of the Valencian Community (Spain)

This work focuses on the situation of the technological transition to new technologies in drip irrigation in the Valencian Community (Spain). The study covers the last decade with data from interviews to managers of Irrigation Communities in 2010 and 2018. We analyze the main technological problems in seven topics: (i) Catchment & Pumping; (ii) Storage & Regulation; (iii) Treatment & Filtering; (iv) Transport & Distribution; (v) Maneuver, Regulation & Protection; (vi) Automation; (vii) Theft and Vandalism. We also have researched the influence of the performance of the Automation system, the presence of a technician in the Irrigation Community and the use of sensors or climatic data. Results show that problems related to technological maintenance of filtering systems or automation are very common and important and they are more important in large Irrigation Communities. We have also observed that mostly large ICs are using sensors or climatic data for their irrigation schedule. We can conclude that their current situation is focused in the daily maintenance of technological problems, inherited from the first modernization processes at the beginning of 21st century. Hence, they are far away from a second stage of modernization or the smart irrigation pushed by the new advances on technology.
The Influence of Staff Competency of Integrated Service in Handling of Poverty

Law No. 11/2009 has stated that the implementation of social welfare carried out by the central and regional government and the community must be directed, sustainable and integrated. The government made a breakthrough in the form of an integrated service and referral system as one of the important instruments in improving the welfare of the poor. The Integrated Service and Referral System (ISRS) according to the Regulation of the Minister of Social Affairs No. 15 of 2018 is a service system that identifies the needs and complaints of the poor and poor people and makes referrals to program managers handling the poor and disadvantaged people at the center and the regions. ISRS in Regency/City began to grow in 2016 after previously conducted research from 2013 under the name "Pandu Gempita". The main objective of this research is to provide input to the government in improving the quality of ISRS services for the poor. The approach used in this study is a mixed method (quantitative and qualitative). The lesson that can be drawn from this study is that the competency of staff has a very high influence in improving services to the poor. Therefore in an effort to improve ISRS services, staff competence must be increased which consists of motivation, attitude, self-concept, science and skills with priority scale that takes into account the results of the research. Keywords—system, referral, integrated, competence
Social and Demographic Predictors of Consumers’ Word of Mouth Engagement in Czechia

Abstract Given that consumers’ Word of Mouth (WOM) communication is influenced by demographic and social background this study investigates (1) to what extent consumers’ WOM engagement is influenced by social relationship variables, (2) in what capacity demographic factors affects preferences to engage in WOM and (3) the preferred WOM environment. Our findings indicate that offline context is preferred, trust and social ties are positively related to WOM, whilst homophily has reportedly negative impact. Age, gender, and education are reported to influence consumers’ propensity to engage in WOM. Based on the results, several practical and theoretical implications are discussed.
Mathematical analysis on the dynamics of COVID-19 in India using SIR Epidemic Model

The Coronavirus Disease (COVID-19) outbreak as on 9th July 2020 has invaded around 12.3 million population causing over half a million deaths worldwide and counting. The entire scientific community has joined hands to find a vaccine for this deadly virus that causes the respiratory illness, COVID-19 in humans. To understand the dynamics of this communicable disease and its transmission among the people in India, a mathematical model governed by ordinary differential equations with ap- propriate conditions has been established. The model is based on SIR (Susceptible-Infected-Removed) scheme to understand the behavior of susceptible, infective and removed (both recovered and deceased) population in India. The resulting model equations have been simulated using MATLAB software. The results obtained in this model were interpreted graphically and least squares method was used to predict the transmission rate, recovery rate and mortality rate in the absence of any vaccine/immunization.