Miracle-dz/UniFAR-FTUs huggingface dataset:
Knowledge, Attitude and Practice on Regenerative Endodontics among Endodontists of Nepal

INTRODUCTION: Regenerative Endodontics is one of the most fascinating development in modern dentistry. Since Endodontists are the first providers of this type of dental treatment, it is essential to learn their knowledge, attitude and practice of these procedures. Aim: This online questionnaire-based study was conducted amongst Endodontists practicing in Nepal with the aim to learn their knowledge, attitude and practice of regenerative endodontic procedures. MATERIALS AND METHODS: A cross-sectional study was conducted among Endodontists in Nepal. In total 65 Endodontists participated in this study. The questionnaire was distributed to the participants using the available electronic measures. Descriptive statistical analyses were performed on the responses given by Endodontists using SPSS Statistical Software package (version 21.0). RESULTS: A total of 20 questions were included in this study. Out of the responses analyzed, 100% (n=65) had come across the term regenerative endodontics. Respondents had good knowledge about the sources of dental stem cells (87.3%, n=55). A high percentage (98.4%, n=62) of respondents strongly recommended regenerative therapy to be incorporated into dentistry. Among the participants of this study, 87.1% (n=54) had a belief that regenerative endodontic treatment could serve as the alternative treatment option to dental implant. CONCLUSIONS: The Endodontists practicing in Nepal had sound knowledge about regenerative endodontic procedures. They were enthusiastic in practicing regenerative endodontics and interested in stem cell therapy. It’s a high time to uplift the regenerative endodontic procedure from simple revascularization via blood clotting to more advanced procedure.
Monitoring of Construction Activity by Change Detection on SAR Time Series Using Coherent Scatterers

In this article, a novel synthetic aperture radar (SAR) change detection method for the monitoring of man-made objects (MMOs) is presented. Rather than looking for changes in SAR amplitude or the loss of coherence, changes are detected by the appearance and disappearance of the strong point scatterers present in MMOs and often denoted as coherent scatterers (CSs). This enables the detection of changes involving MMOs while ignoring changes to natural targets such as vegetation. These CSs are detected in each image and compared coherently across an image pair or a time series. When using a time series, the proposed method can categorize the changes according to their temporal behavior. An object-based change analysis step for identifying changes significantly larger than individual CSs is also introduced. The proposed approach is applied for the monitoring of construction activity using a time series of 49 TerraSAR-X images of the city of Munich.
TDLAS Monitoring of Carbon Dioxide with Temperature Compensation in Power Plant Exhausts

Temperature variations of flue gas have an effect on carbon dioxide (CO2) emissions monitoring. This paper demonstrates accurate CO2 concentration measurement using tunable diode laser absorption spectroscopy (TDLAS) with temperature compensation methods. A distributed feedback diode laser at 1579 nm was chosen as the laser source for CO2 measurements. A modeled flue gas was made referring to CO2 concentrations of 10–20% and temperatures of 298–338 K in the exhaust of a power plant. Two temperature compensation methods based on direct absorption (DA) and wavelength modulation (WMS) are presented to improve the accuracy of the concentration measurement. The relative standard deviations of DA and WMS measurements of concentration were reduced from 0.84% and 0.35% to 0.42% and 0.31%, respectively. Our experimental results have validated the rationality of temperature compensations and can be further applied for high-precision measurement of gas concentrations in industrial emission monitoring.
Object-Cooperated Ternary Tree Partitioning Decision Method for Versatile Video Coding

In this paper, we propose an object-cooperated decision method for efficient ternary tree (TT) partitioning that reduces the encoding complexity of versatile video coding (VVC). In most previous studies, the VVC complexity was reduced using decision schemes based on the encoding context, which do not apply object detecion models. We assume that high-level objects are important for deciding whether complex TT partitioning is required because they can provide hints on the characteristics of a video. Herein, we apply an object detection model that discovers and extracts the high-level object features—the number and ratio of objects from frames in a video sequence. Using the extracted features, we propose machine learning (ML)-based classifiers for each TT-split direction to efficiently reduce the encoding complexity of VVC and decide whether the TT-split process can be skipped in the vertical or horizontal direction. The TT-split decision of classifiers is formulated as a binary classification problem. Experimental results show that the proposed method more effectively decreases the encoding complexity of VVC than a state-of-the-art model based on ML.
Modelling polarized light for computer graphics

The quality of visual realism in computer generated images is largely determined by the accuracy of the reflection model. Advances in global illumination techniques have removed to a large extent, some of the limitations on the physical correctness achievable by reflection models. While models currently used by researchers are physically based, most approaches have ignored the polarization of light. The few previous efforts addressing the polarization of light were hampered by inherently unphysical light transport algorithms. This paper, besides taking polarization of light into account in the reflection computation, also provides a basis for modelling polarization as an inherent attribute of light, using the Stokes parameters. A reflection model is developed within this framework and the implementation within a global illumination algorithm called Photon is presented.
Decreased Postural Sway in Women Who Are Visually Impaired: Is it a Learned Protective Mechanism?

Introduction: Comparison of sway parameters of visually impaired participants to that of the sighted population may give insight into the intrinsic risk of falls relative to the surface. Sway is a natural mechanism to adjust the posture and maintain balance. But the sway characteristics on uneven surfaces are ill explored. There is a paucity of evidence on baseline values of sway amplitude in visually impaired women in comparison to sighted women, which underpins the importance of this study. Methods: Eighteen visually impaired young women and an equal number of age-matched sighted peers were recruited by convenience to this prospective observational study. Sway amplitude of the participants were measured using a sway meter on three different surfaces, with eyes opened and closed conditions, using videography and analyzed using Kinovea motion analyzing software. Demographics and participant characteristics were summarized using descriptive statistics. The comparison were performed using independent sample t-test. Results: Visually impaired women demonstrated lower amplitude of sway than sighted young women, irrespective of the surface. Discussion: There was a gradual increase in sway amplitude as the standing surfaces changed from even to sand and pebbles, respectively, for both groups. Implications for Practitioners: Contrary to the existing evidence, the results of this study indicate that visually impaired young individuals may not be not at higher intrinsic risk of falls on various terrains than their sighted peers. The authors hypothesize that the lower sway among visually impaired participants can be attributed to the learned strategy for safety from exposure to real-life pragmatic environments during everyday activities, which enabled them to adopt postural strategies as a safety measure. Hence, this strategy can potentially be used in dynamic situations to decrease the propensity for falls during ambulation in visually impaired individuals.
Intracity Temperature Estimation by Physics Informed Neural Network Using Modeled Forcing Meteorology and Multispectral Satellite Imagery

Estimating urban surface temperature at high resolution is crucial for effective urban planning for climate-driven risks. This high-resolution surface temperature over broader scales can usually be obtained via satellite remote sensing for historical period. However, it can be hard for future predictions. This article presents a physics informed hierarchical perception (PIHP) network, a novel approach for accurate, high-resolution, and generalizable urban surface temperature estimation. The key to our approach is leveraging the implied temperature-related physics information of the land surface structure from high-resolution multispectral satellite images, thus achieving precise estimation or prediction for high spatial resolution urban surface temperature. Specifically, a semantic category histogram is first designed to describe the land surface structures. Based on this, a hierarchical urban surface perception network is proposed to capture the complex relationship between the underlying land surface features, upper atmosphere conditions, and the intracity temperature. The proposed PIHP-Net makes it possible to generate models that can generalize across different cities, thus estimating or predicting high-resolution urban surface temperature when the satellite land surface temperature (LST) observation is not available. Experiments over various cities in different climate regions in China show, for the first time, errors less than 2 K (for most of the cases) at the high resolution (60-by-60 meters grids), thus making it possible to predict future intracity temperature from forcing meteorology and multispectral satellite imagery.
A 1 THz Schottky transceiver front‐end based on 5 μm GaAs monolithic membrane

A Schottky diode‐based 1 THz Schottky transceiver front end is designed, fabricated, and measured. The terahertz mixer and tripler are fabricated with a 5 μm‐thick GaAs monolithic Schottky technology. Compact passive filter and matching network are designed to reduce the loss of transmission route. At 300 K ambient temperature, the measured minimum double‐side band noise temperature and conversion loss of 1 THz subharmonic mixer are <5000 K and 13 dB, respectively. At self‐developed available pump source, the measured maximum output power of 1 THz monolithic tripler is over 70 μW and the average output power from 960 to 1030 GHz is 35 μW. The accomplished 1 THz monolithic circuits have proved the feasibility of the proposed design process, which have certain reference value for higher frequency solid‐state Schottky‐based circuit.
Function of Molybdenum Insertases

For most organisms molybdenum is essential for life as it is found in the active site of various vitally important molybdenum dependent enzymes (Mo-enzymes). Here, molybdenum is bound to a pterin derivative called molybdopterin (MPT), thus forming the molybdenum cofactor (Moco). Synthesis of Moco involves the consecutive action of numerous enzymatic reaction steps, whereby molybdenum insertases (Mo-insertases) catalyze the final maturation step, i.e., the metal insertion reaction yielding Moco. This final maturation step is subdivided into two partial reactions, each catalyzed by a distinctive Mo-insertase domain. Initially, MPT is adenylylated by the Mo-insertase G-domain, yielding MPT-AMP which is used as substrate by the E-domain. This domain catalyzes the insertion of molybdate into the MPT dithiolene moiety, leading to the formation of Moco-AMP. Finally, the Moco-AMP phosphoanhydride bond is cleaved by the E-domain to liberate Moco from its synthesizing enzyme. Thus formed, Moco is physiologically active and may be incorporated into the different Mo-enzymes or bind to carrier proteins instead.
LNG vapour cloud dispersion modelling and simulations with OpenFOAM

Growth in demand for Liquefied Natural Gas (LNG) has increased calls for further research and development on LNG production and safer methods for its transportation. This paper presents the implementation of numerical models for dispersion of evaporated LNG in the open atmosphere. The developed model incorporates in its formulation LNG spill and pool formation into a source model. It is then coupled with a Computational Fluid Dynamics (CFD) approach in OpenFOAM for dispersion calculations. Atmospheric conditions such as average wind speed and direction were used to resolve wind boundary layers. The model also accounts for the humidity effect and its influence on air-density and buoyancy change. Verifications have been conducted using the experimental results from Maplin Sands series of tests by comparing the maximum evaporated gas concentration in every arc in relation to the release point. The results show good agreements between the model’s predictions and experiments.
Design and control of a climbing robot for inspection of high mast lighting

Purpose This paper aims to develop a climbing robot to help people inspect lamps of high-mast lighting. Design/methodology/approach The robot consists of driving mechanism, suspension mechanism and compression mechanism. The driving mechanism is realized by link chains and sprockets, which are arranged opposite to each other, to form a dual caterpillar mechanism. The compression mechanism squeezes the caterpillar, and rubber feet “grasps” the steel rope to generate enough adhesion forces. The suspension mechanism is used to compensate the contraction or extension of the chains. The robot is equipped with a DC motor with a rated power of 250 W and a wireless module to communicate with the operator’s console. The dynamic model of the robot and the control strategy is derived, and the stability of the controller is proofed. Findings The payload experiment shows the robot can afford up to 3.7 times payload versus its own weight. Even when the payload is 30 kg, the robot can maintain a speed of the 1 m/s. The experiments also show that the tracking error of the robot reaches zero. Practical implications The proposed moving mechanism has a high load/weight ratio, which is a verified solution for the cable inspection purpose. Originality/value A rope climbing robot for high mast lighting inspection is proposed. The developed mechanism can reach a speed of 1 m/s with the payload of 30 kg, while its own weight is only 15.6 kg. The payload/weight ratio of the robot is 2.24; this value is rather good in many climbing robots reported in other renowned journal.
Antagonism of nonaflatoxigenic Aspergillus flavus isolated from peanuts against aflatoxigenic A. flavus growth and aflatoxin B1 production in vitro

Abstract Aspergillus section Flavi constitutes several species of opportunistic fungi, notable among them are A. flavus and A. parasiticus, capable of surviving harsh conditions and colonizing a wide range of agricultural products pre‐ and postharvest. Physical and chemical control methods are widely applied in order to mitigate the invasion of A. flavus in crops. However, physical control is not suitable for large scale and chemical control often leads to environmental pollution, whereas biological control offers a safer, environmentally friendly, and economical alternative. The present study aimed to investigate the antagonism of several non‐aflatoxigenic A. flavus strains against the aflatoxigenic ones in vitro (semisynthetic peanut growth medium; MPA) in terms of colony growth rate and AFB1 inhibition. Different peanut concentrations were used to obtain the optimum peanut concentration in the formulated growth medium. A dual culture assay was performed to assess the antagonism of nonaflatoxigenic strains against the aflatoxigenic ones. Results revealed that 9% MPA exhibited the highest growth and AFB1 inhibition by nonaflatoxigenic strains. It was also found that different nonaflatoxigenic strains exhibited different antagonism against the aflatoxigenic ones which ranged from 11.09 ± 0.65% to 14.06 ± 0.14% for growth inhibition, and 53.97 ± 2.46% to 72.64 ± 4.54% for AFB1 inhibition. This variability could be due to the difference in antagonistic metabolites produced by different nonaflatoxigenic strains assessed in the present study. Metabolomics study to ascertain the specific metabolites that conferred the growth and aflatoxin inhibition is ongoing.
An Application of a Novel Technique for Assessing the Operating Performance of Existing Cooling Systems on a University Campus

Optimal operation is an important aspect of energy efficiency that can be employed to reduce power consumption. In cooling systems, the chillers consume a large amount of electricity, especially if they are not optimally operated, therefore, they cannot produce the required or rated cooling load capacity. The objective of this paper is to improve coefficient of performance (COP) for the operation of chillers and to reduce power consumption. Two contributions in this work are: (1) the prediction of a model by using Adaptive Neuro-Fuzzy Inference System (ANFIS)-based Fuzzy Clustering Subtractive (FCS), and (2) the classification and optimization of the predicted models by using an Accelerated Particle Swarm Optimization (APSO) algorithm. Particularly, in contribution (1), two models are developed to predict/assess power consumption and cooling load capacity. While in contribution (2), the predictive model’s data obtained are used to classify the operating performance of the chiller and to optimize the model in order to reduce power consumption and cooling capacity. Therefore, data classification by APSO is used to enhance the coefficient of performance (COP). The proposed technique reduces the total power consumption by 33.2% and meets the cooling demand requirements. Also, it improves the cooling performance based on COP, thus resulting in a 15.95% increase in efficiency compared to the existing cooling system. The studied ANFIS-based FCS outperforms the ANFIS-based fuzzy C-means clustering in terms of the regression. Then, the algorithm-based classifier APSO has better results compared to the conventional particle swarm optimization (PSO). The data was acquired from the District Cooling System (DCS) at the Universiti Teknologi Petronas (UTP) campus in Malaysia.
Complications in patients with COVID-19 in a cohort of intensive care hospitalists

This article aims to identify the complications presented in patients with COVID-19 during their stay in intensive care. We conducted a retrospective documentary cohort study in medical records of adults admitted to an Intensive Care Unit designated for the treatment of COVID-19 patients, from September 2020 to January 2021. The sample consisted of 47 medical records of patients over 18 years old, with confirmed diagnosis for SARS-COV-219 by reverse transcription test and polymerase chain reaction. Medical records of 24 women (51,1%) and 23 men (49,9%) were included in the study, with an average of 70 years old. The main complications described involved the blood, immune and respiratory systems. Electrolyte disorder was the most frequent complication observed in 100% of the patients, followed by leukocytosis (95,7%), acid-base disorder and acute respiratory failure, present in 87,2% of the analysed cases. We conclude that COVID-19 causes damage to multiple systems, directly affecting the prognosis of patients.
Runner optimal position in a gravitational water vortex hydraulic turbine with spiral inlet channel and a conical basin

A gravitational water vortex hydraulic turbine (GWVHT) is a low head hydropower technology with a vertical runner for extracting energy from the water vortex. To determine the optimal position (h) of the runner for the hydropower plant efficiency to be increased, a runner in three different positions was compared using computational fluid dynamics (CFD). The position of the runner was a function of the basin height (H). The maximum efficiency (44.15%) was established when the runner was located at 60% of H. The angular velocity associated with the maximum efficiency was 14 rad/s.
Integrating Mindfulness and Acceptance Into Traditional Cognitive Behavioral Therapy During the COVID-19 Pandemic: A Case Study of an Adult Man With Generalized Anxiety Disorder

Generalized Anxiety Disorder (GAD) can be chronic and impairing, highlighting the need for effective treatments. Although Cognitive Behavior Therapy (CBT) is an effective treatment for GAD, a number of patients continue to report GAD symptoms treatment. Integrating evidenced-based treatment components into CBT treatments, such as mindfulness- and acceptance-based treatment components found in Acceptance and Commitment Therapy (ACT), may help improve the efficacy of treatment. Emerging interventions and research suggest that the cognitive restructuring aspect of CBT and acceptance stance of ACT (e.g., cognitive defusion) can be implemented into treatment concurrently from a stance of increasing a patient’s coping skills repertoire and psychological flexibility. This systemic case analysis examined the efficacy and clinical utility of integrating ACT into a manualized CBT treatment for GAD. Furthermore, this study examined treatment efficacy and therapeutic alliance as the treatment rapidly and unexpectedly transitioned from in-person to telehealth due to the COVID-19 pandemic. Pre- to post-treatment and time-series analyses showed significant decreases in anxiety symptoms, worry, depressive symptoms, and emotion dysregulation. Although there was an initial increase in depressive and anxiety symptoms, worry, and emotion dysregulation following the switch from in-person to telehealth services, these quickly subsided and resumed a downward trend. The therapeutic relationship did not deteriorate during the transition to telehealth. This case study provides evidence of feasibility and efficacy of an integrated CBT/ACT approach in treating GAD. It also suggests that despite some temporary increase in symptoms, therapeutic alliance and treatment efficacy were not impacted by the switch to telehealth.
Omc: AN Optical Monitoring Camera for Integral

The INTEGRAL payload has been designed to study simultaneously gamma-ray sources in a wide field of view over many decades in energy (around 2 eV + 4 keV − 20 MeV) and thus make a major contribution to short time-scale high-energy astrophysics. The OMC will observe the optical emission from the prime targets of the gamma-ray instruments with the support of the x-ray monitor. This capability will provide invaluable diagnostic information on the nature and the physics of the sources over a broad wavelength range. The main scientific objectives will be: (1) to monitor the optical emission from the sources observed by the gamma- and x-ray instruments, measuring the time and intensity structure of the optical emission for comparison with variability at high energies, and (2) to provide the brightness and position of the optical counterpart of any gamma- or x-ray transient taking place within its field of view. The OMC will be based on a refractive optics with an aperture of 50 mm focused onto a large format CCD (1024 × 2048 pixels) working in frame transfer mode (1024 × 1024 pixels imaging area). With a field of view of 5° × 5° it will be able to monitor sources down to V = 19 mag. Typical exposures will consist of 10 integrations of 100 seconds each.