Miracle-dz/UniFAR-FTUs huggingface dataset:
Patterns of Parental Information Seeking Behavior on Early Childhood Caries: A Qualitative Exploration

Objectives: This study aims to explore the information-seeking behavior patterns of parents with children receiving treatment for early childhood caries (ECC). Materials and Methods: Semistructured in-depth interviews were conducted with 20 parents of children with ECC. A topic guide was developed, focusing on questions relating to (i) the timing of their seeking information on ECC, (ii) the types of EEC information they seek, and (iii) the resources used to seek information. The interviews were audio-recorded and transcribed verbatim. Thematic analysis was performed, whereby the data were coded and categorized into themes and subthemes. Results: Four main themes were identified: the immediacy of seeking information, perceived information need, use of resources, and barriers to seeking information. Parents either sought information immediately after detecting changes to the appearance of their child’s teeth, with some being aware of the changes after signs and symptoms developed. The types of information parents usually sought covered the disease, its prevention, and management. Common sources of information were friends, family, the internet, and healthcare professionals. Barriers to seeking information discussed by parents were lack of time as well as insufficiency and inaccuracy of the information they received. Conclusion: This study highlighted the need for comprehensive, tailored early education on ECC for parents using reliable information sources. There is also a need to empower other nondental healthcare professionals to provide oral healthcare education for parents.
Research on Traffic Scene Recognition Algorithm Combining Object Detection and Semantic Segmentation

: At present, the detection of instances in traffic scenes based on deep learning is mainly divided into two mainstream directions: object detection and semantic segmentation. Among them, object detection realizes the specific location of a single object in the road scene, and semantic segmentation realizes the pixel level classification of objects and background categories in the road scene. However, when pedestrian and other objects have occlusion problems, semantic segmentation is difficult to directly separate a single instance, and the anchor frame generated by object detection contains redundant information. To solve this problem, this paper proposes a method combining target detection and semantic segmentation. This method first uses YOLOv5 model to complete the target detection, and detects people, vehicles and other objects in the captured traffic scene image. At the same time, the improved DeepLabv3+ network model is used to capture the semantic and regional information of roads in the captured traffic scene image. Finally, the prediction results of the output of the two task branches are drawn in the image to be detected, and finally the drawing results are combined and output uniformly. This method can effectively distinguish different people, vehicles, roads and other information in the traffic scene, "complement each other" to understand the driverless road scene, and improve the detection accuracy. The experimental results show that the average mAP of this method is 79.11%, and the segmentation accuracy is high, which is suitable for the unmanned driving scene on real urban roads.
Rational Addiction and Cigarette in the Context of Health Economics—A Literature Review

: As a typical addictive consumption, cigarettes play a special role in socio-economic activities. The dual addictive characteristics of cigarette consumption make it both an income effect and a health loss effect, which has an important impact on the operation of the social economy: on the one hand, the sociable consumption of the group can maintain or strengthen the social network may bring an increase in income, that is, the income effect; on the other hand, excessive smoking makes the body much more likely to suffer from various chronic diseases, increasing the social health expenditure, and there is a health loss effect. This literature review illustrates the relationship between cigarette consumption and rational addiction behavior. I chose the base paper written by Gary S. Becker, Michael Grossman, and Kevin M. Murphy and titled "An Empirical Analysis of Cigarette consumption. " The article concentrates on the smoking addiction problem and uses statistical models to collect data in the USA. Since the smoking addiction problems gets more and more serious, the paper plays an essential role in the policy planning by understanding the cigarette demand.
On the mean-square rate of convergence of temporal-difference learning algorithms

In this paper, the mean-square rate of convergence of temporal-difference learning algorithms is analyzed. The analysis is carried out for the case of discounted cost function associated with a Markov chain with a finite dimensional state-space. Under mild conditions, it is shown that these algorithms converge at the rate O(n/sup -1/2/). The results are illustrated with examples related to random coefficient autoregression models and M/G/1 queues.
A Retrospective Study on the Complications of Ilizarov Technique in the Treatment of Neurogenic Talipes Equinovarus

In order to discuss the postoperative complications of Ilizarov technique in the treatment of neurogenic talipes equinovarus, we conducted a retrospective study on the postoperative complications of neurogenic talipes equinovarus patients treated with Ilizarov technique from January 2013 to December 2020.
Identifying the Optimal Machine Learning Model for Predicting Car Insurance Claims: A Comparative Study Utilising Advanced Techniques

: This study presents an investigation into the use of machine learning techniques for predicting car insurance claims, with a specific focus on identifying the optimal model for this task. By utilising advanced techniques such as SMOTEEN, ANOVA, and Chi-squared tests, the challenge of processing imbalanced data and identifying relevant features were addressed. Our evaluation of five popular and effective models, including logistic regression (LR), random forest (RF), support vector machine (SVM), multi-layer perceptron (MLP), and extreme gradient boosting (XGBoost), yields result that demonstrate the superiority of the RF model in predicting car insurance claims. Furthermore, our study illustrates the advantages of using machine learning algorithms in handling large and complex datasets, making predictions on future insurance claims, and adapting to changing circumstances, making it a valuable tool for practitioners in the insurance industry.
Axiomatic G1-vertex algebras

Inspired by Borcherds' work on "G-vertex algebras," we formulate and study an axiomatic counterpart of Borcherds' notion of G-vertex algebra for the simplest nontrivial elementary vertex group, which we denote by G1. Specifically, we formulate a notion of axiomatic G1-vertex algebra, prove certain basic properties and give certain examples, where the notion of axiomatic G1-vertex algebra is a nonlocal generalization of the notion of vertex algebra. We also show how to construct axiomatic G1-vertex algebras from a set of compatible G1-vertex operators.
A Study of American Response to Climate Change and the Influence of Carbon Dependency, Social Capital, and Political Orientation

Abstract Climate change is one major challenge that has brought substantial costs to the United States. To implement mitigation measures and gain public support, it is critical to understand Americans’ attitudes toward this issue. Our study investigates how carbon dependency, social capital, and political orientation influence public response to climate change by perceiving its threat, changing behaviors, and supporting policies. We first build an integrative paradigm to explore the theoretical connections. Next, we employ data from different sources to measure these key concepts at individual and state levels and then estimate the relationships empirically. Multilevel regression results show that carbon dependency inhibits public response while social capital enhances such response. Democrats and liberals are motivated to respond and residents of Democratic Party controlled states are also more likely to believe in climate change and perceive the risk than their counterparts. These factors can be leveraged to mobilize public engagement in climate activism.
Time-varying effects of economic policy uncertainty on commodity prices in China: an empirical analysis based on the TVP-SVAR-SV model

: Based on data from March 2008 to June 2020, we use the TVP-SVAR-SV model to study the time-varying impact of economic policy uncertainty on Chinese commodity prices and analyze the effect of economic policy uncertainty on Chinese commodity prices in different periods. The results show that: Firstly, economic policy uncertainty has a significant time-varying impact effect on Chinese commodity prices, and the short-term effect is larger than the long-term effect. Secondly, economic policy uncertainty positively affects Chinese commodity prices during the Chinese stock market crash in June 2015; economic policy uncertainty negatively affects Chinese commodity prices during the global financial crisis in December 2008 and the COVID-19 outbreak in December 2019, and the negative effect is greater during the global financial crisis in December 2008.
zur Erlangung des akademischen Grades Diplom-Mathematiker

We propose a new method of combining ranking results which each rank the same set of items according to different criteria. It will choose a ranking that is closest as possible to each ranking result to be combined. In the context of the Internet, it can be used to rank web pages into an order that best reflects a balance between several criteria. In the context of sports, we propose to use the method to determine the winner of competitions, when the performance of an athlete is naturally judged according to different criteria, such as figure skating and show jumping. The rank aggregation method we propose is known to be NP-hard. This thesis aims to develop efficient algorithms to compute aggregated rankings for practically relevant instances. By employing parameterized complexity theory, we can identify the structural hardness of an instance and allow for choosing a high-performing algorithm accordingly. We present efficient and effective data reduction rules which will reduce parameters measuring the structural difficulty of an instance provably by simplifying the instance or removing unneeded parts. We provide efficient search tree algorithms which will solve practically relevant instances, where the criteria correlate strongly. Experiments with synthetic data confirm that for instances with high correlation between the rankings, even large instances can be computed in short time. For general instances, we present two enumeration algorithms, which will likely outperform the trivial algorithm of trying all rankings and comparing their qualities as aggregations. We prove the enumeration algorithms to perform well in scenarios with both few items to be ranked and some correlation between the rankings. We present methods to approximate the solution quality by a factor of two. We present parameters which can not be used to improve computation by proving and we will prove the NP-hardness of the problem even for small values of these parameters.
Effects of the Written Test Form and Content with Pragmatic Meaning in the Validity of English Speech Test

: Many teacher-training universities only adopt a single form (read aloud) and content without pragmatic meaning in English Speech Test. However, some scholars show queries on this issue because they worry about whether a single form (read aloud) and content without pragmatic meaning bring about low validity or not. This essay focuses on effects of the written test form and content with pragmatic meaning in the validity of English Speech Test. And through the experiment and analysis, it can be seen that when the written test form and content with pragmatic meaning are added, it comparatively whether plays an important role in English Speech Test or not.
Chemins minimaux et modèles déformables en analyse d'images

Nous presentons une synthese d'une partie de nos travaux sur les chemins minimaux. Introduits au depart pour trouver le minimum global de l'energie pour les contours actifs a l'aide du Fast Marching [18], nous les avons utilises par la suite pour la recherche de contours multiples pour completer des points, des courbes ou des regions dans des images 2D et 3D. Plusieurs variantes permettent d'ameliorer le temps de calcul, de simplifier l'initialisation ou de centrer le chemin dans une structure tubulaire. Le Fast Marching est aussi un moyen efficace de resoudre l'evolution d'un modele de contour actif ballon par level sets. Nous montrons des applications notamment pour la segmentation de routes et vaisseaux et pour l'endoscopie virtuelle.
Super bowl ads in the period from 2017-2022

Advertising during Super Bowl commercial breaks has become a crucial part of brands' marketing strategies, offering them the chance to reach a huge audience. Over the past six years, Super Bowl ads have been diverse and captivating, showcasing products from various categories such as food and beverage, cars, beer and financial and online services. The article provides a brief and overall analysis of Super Bowl ads from 2017 to 2022. The database used in the analysis was taken from the world-famous database at adsoftheword.com. This research analyzed the length, logo viewability and product category, presence of celebrities, animals, humor and the average likability score from Ad meter in Super Bowl ads from 2017 to 2022. This analysis shows the changes in marketing strategies highlighting the growing sophistication of the advertising industry.
Research progress of temporomandibular joint in adolescent malocclusion

: The prevalence of malocclusion in permanent dentition was 72.97%. Temporomandibular joint (TMJ) is one of the most important joints in human body, and its functional structure is the most complex. The shape and position of the temporomandibular joint in patients with malocclusion were affected by occlusal occlusion. This review focuses on the effects of different types of malocclusion on the morphology and function of temporomandibular joint (TMJ) in adolescents
Combined Forecasts of Intermittent Demand for Stock-keeping Units (SKUs)

Effective inventory management requires accurate forecasts for stock-keeping units (SKUs), especially for the strategic ones for companies’ operations and after-sales services like providing spare parts. Forecasting is a challenging task for such SKUs as they usually have intermittent demand (ID) patterns, consisting of many periods with zero demand and infrequent demand arrivals. Given the highly uncertain nature of ID for SKUs, this study developed a methodological framework for combining statistical and judgmental forecasts and assessed the performance of the proposed framework by using accuracy and bias measures. The forecasting process has several steps, including data preparation, data categorization based on demand patterns, generating statistical and judgmental forecasts, combining statistical and judgmental forecasts, and evaluating the forecast performance. These steps were illustrated on a real-world dataset that contains monthly customer demand data for after-sales spare parts. Results showed that combination is the best method for the majority of SKUs. This paper contributes to the limited literature by addressing the gap between the combined and ID forecasts. The proposed framework gives practitioners and researchers a comprehensive overview to help them make more accurate forecasts while encouraging the use of simple but structured approaches.
Characteristics of Export-oriented Technological Progress and Total Factor Productivity of China's Manufacturing Industry

: Since the reform and opening up, it is an important means of industrial technology innovation in China to realize technology upgrading by introducing and imitating innovation. The characteristics of the supply of technical elements and the demand of technical products "both ends are outside" constitute the export-oriented technological progress mode of China's industrial technological innovation . In this paper, the export-oriented technology progress of China's manufacturing industry from 1992 to 2020 is divided into three stages, and the DEA-Malmquist method is used to measure the total factor productivity changes of 26 manufacturing industries in China during this period. The results show that from 1992 to 2000, the total factor productivity index of China's manufacturing industry showed a fluctuating trend during the period of high economic growth driven by accelerated export expansion. During the period of optimizing commodity structure and promoting industrial upgrading from 2001 to 2011, the total factor productivity index of China's manufacturing industry first increased steadily, and then decreased from 2008 to 2011. Since 2012, in the stage of building a trade powerful country and promoting innovation, the total factor productivity of China's manufacturing industry has entered the growth stage again in 2016 after a period of decline. Finally, this paper puts forward some suggestions.
Antioxidant Activity of Aqueous Extract of Spatholobi Caulis and Its Ameliorative Effect on CCl4 Induced Acute Liver Injury in Mice

: The acute liver injury model of mice induced by carbon tetrachloride (CCl 4 ) was used to explore the protective effect of aqueous extract of Spatholobi Caulis on acute liver injury. Methods: The contents of total phenols and total flavonoids in the aqueous and ethanol extracts of Caulis spatholobi were determined, and the antioxidant activity was evaluated by DPPH, ABTS free radical scavenging rate and FRAP total reducing capacity. 30 C57BL/6J male mice were randomly divided into model group, bifendate group, the low-dose, medium-dose and high-dose groups of aqueous extract of Spatholobi Caulis (n = 6). The animal model of acute liver injury was established by intraperitoneal injection of CCl 4 after 7 days with corresponding drugs. The pathological changes of liver tissue were observed by H&E staining. Serum levels of interleukin-1β (IL-1β), interleukin-6 (IL-6), interleukin-10 (IL-10) and tumor necrosis factor α (TNF-α) were determined by ELISA. The indexes of alanine aminotransferase (ALT), aspartate aminotransferase (AST) and antioxidant effects of catalase (CAT), superoxide dismutase (SOD), glutathione peroxidase (GSH-Px) and malondialdehyde (MDA) were determined. Results: Liver histomorphology observation showed that aqueous extract of Spatholobi Caulis could significantly improve liver cell injury and inflammatory cell infiltration, and significantly increased the activities of CAT, SOD and GSH-Px antioxidant enzymes in liver, decreased the contents of MDA and ALT and AST in serum, significantly down-regulated the levels of IL-1β, IL-6 and TNF-α in serum, and up-regulated the levels of IL-10 and other inflammatory factors. Conclusion: The aqueous extract of Spatholobi Caulis can improve acute liver injury induced by CCl 4 in mice through improving antioxidant and anti-inflammatory effects.
Application of Metabolomics in Oral Cancer

: As an extension and terminal of genomics and proteomics, metabolomics has recently become a research focus of disease prevention, pathogenesis and disease diagnosis. With the development of metabolomics, its research in oral cancer and potential malignant lesions of oral cavity can provide important reference materials for laboratory and clinical practice. This paper reviews the theoretical basis of metabolomics, detection methods and analysis methods in oral cancer and potential malignant lesions of oral cavity.
Factors Influencing Online Purchase Intention among Students in SEGI University

: In recent years, some college students, represented by Generation Y (millennial generation) and Generation Z, have become important shopping groups due to their high computer literacy and Internet proficiency. Even after the implementation of COVID-19 in 2020, Malaysia's e-commerce is expanding rapidly, but it faces challenges. The purpose of this study is to explore the perceived usefulness of shoppers' purchasing intention. In addition, the researcher focused on the connection between the perceived usefulness and the buyer's purchase intention. In this study, a simple random sampling technique was used. The researcher gathered substantial reactions from understudies at Malaysia's SEGi University utilizing a four-sections questions by using Google Form. Then, at this point, SPSS 26.0 and SmartsPLS were used to decompose the collected information. As per the study results, perceived usefulness and perceived ease of use impact buyers' readiness to shop on the web. Therefore, in order to further develop intensity, online retailers and advertisers should pay more attention to the usability and ease of use. Gradually, the exploration results of H1 and H2 showed that perceived usefulness and perceived ease of use have fundamentally affected the audience's ability to purchase online.
Effect of abnormal occlusal contact on temporomandibular joint

: Occlusion, temporomandibular joint and masticatory muscle are in a functional system, which cooperate and influence each other. When any one of these elements is abnormal, it will affect the function of other elements. The normal occlusal relationship is the convex-concave relationship of apical fossa contact, and the masticatory movement trajectory is teardrop-like, which is helpful to promote the normal mandibular functional movement. The abnormal occlusal contact relationship changes the convex-concave relationship of apical fossa contact into convex relationship, which will form abnormal masticatory movement trajectory, and may even cause abnormal movement and stress of temporomandibular joint and abnormal contractile activity of masticatory muscle. The longer the duration of this abnormal occlusal relationship, the greater the damage to bone and soft tissue. scissors bite, openbite and crossbite are common occlusal abnormalities in clinic, so this article will focus on the effects of these three abnormal occlusal contacts on the temporomandibular joint.
Tropical Storm Development and Decay: Sensitivity to Surface Boundary Conditions

Abstract Hurricane models have rarely been used to investigate the observational fact that tropical disturbances seldom form, develop, or intensify over land. Furthermore, rather ad hoc assumptions have been made when modeling landfall. The general consensus is that energy supplied primarily through surface fluxes is necessary for tropical cyclone development and maintenance. In the past, rather a priori assumptions have been made such as the elimination of surface sensible and latent heat fluxes over land or the reduction of surface land temperature. By incorporating an improved version of the Geophysical Fluid Dynamics Laboratory (GFDL) tropical cyclone model with diurnal radiation and a bulk subsurface layer with explicit prediction of land temperature, a series of experiments was performed to test the sensitivity of surface boundary conditions to tropical cyclone development and decay at landfall. A triply nested version of the GFDL model was used in an idealized setting in which a tropical disturbanc.