Miracle-dz/UniFAR-FTUs huggingface dataset:
Effect of Fixed Orthodontic Treatment on Salivary Flow, pH and Microbial Count

Objectives: The present study was designed to evaluate the changes in saliva properties and oral microbial flora in patients undergoing fixed orthodontic treatment. Materials and Methods: Two important saliva properties namely the salivary flow rate and pH as well as oral microbial flora were assessed in 30 orthodontic patients before starting fixed orthodontic treatment and after six, 12 and 18 weeks of treatment. Selective media, Sabouraud dextrose agar, Mitis salivarius agar and Rogosa agar were used for isolation of Candida albicans, Streptococcus mutans and Lactobacillus acidophilus, respectively. Statistical analysis was performed using Friedman and Dunn’s tests. P< 0.05 was considered statistically significant. Results: After six, 12 and 18 weeks of commencing fixed orthodontic treatment, the total colony counts of Candida albicans, Streptococcus mutans and Lactobacillus acidophilus showed a significant increase. The saliva pH decreased during the orthodontic treatment (P< 0.05) while the salivary flow did not change significantly. Conclusions: Fixed orthodontic treatment causes major changes in the saliva properties. The changes in oral microflora and saliva properties show the importance of caries preventive measures during orthodontic treatment.
Controlling Buoyancy-Driven Profiling Floats for Applications in Ocean Observation

Establishing a persistent presence in the ocean with an autonomous underwater vehicle (AUV) capable of observing temporal variability of large-scale ocean processes requires a unique sensor platform. In this paper, we examine the utility of vehicles that can only control their depth in the water column for such extended deployments. We present a strategy that utilizes ocean model predictions to facilitate a basic level of autonomy and enables general control for these profiling floats. The proposed method is based on experimentally validated techniques for utilizing ocean current models to control autonomous gliders. With the appropriate vertical actuation, and utilizing spatio-temporal variations in water speed and direction, we show that general controllability results can be met. First, we apply an A* planner to a local controllability map generated from predictions of ocean currents. This computes a path between start and goal waypoints that has the highest likelihood of successful execution. A computed depth plan is generated with a model-predictive controller (MPC), and selects the depths for the vehicle so that ambient currents guide it toward the goal. Mission constraints are included to simulate and motivate a practical data collection mission. Results are presented in simulation for a mission off the coast of Los Angeles, CA, USA, that show encouraging results in the ability of a drifting vehicle to reach a desired location.
Numerical Simulation for a Droplet Fission Process of Electrowetting on Dielectric Device

Electrowetting has been proposed as a technique for manipulating droplets surrounded by air or oil. In this paper, we discuss the modeling and simulation of the droplet fission process between two parallel plates inside an electrowetting on dielectric (EWOD) device. Since the gap between the plates is small, we use the two-phase Hele-Shaw flow as a model. An immersed boundary (IB) method is employed to solve the governing equations and a local level set method is used to track the drop interface. For comparison purposes, the same set of two-phase HeleShaw equations are also solved directly using the ghost-fluid (GF) method. Numerical results are consistent with experimental observations reported in the literature, provided that care is taken to treat the contact angle.
CORDIC and SVD implementation in digital hardware

Singular Value Decomposition is classified among the most effective numeric methods of matrices inversion. The paper presents a study of hardware implementation of SVD and CORDIC algorithms. Various digital architectures were proposed and compared, including low-cost sequential and high-performance pipelined solutions. Fixed point and floating point arithmetic was considered. The concepts were implemented in VHDL, verified and synthesized with Xilinx tools. Selected approach was physically implemented and tested.
Optimized triangle mesh compression using prediction trees

Recently, a wealth of algorithms for the efficient coding of 3D triangle meshes have been published. All these focus on achieving the most compact code for the connectivity data. The geometric data, i.e. the vertex coordinates, are then coded in an order induced by the connectivity code, which is probably not optimal. This is a pity, as the geometric portion of the data set dominates the code. We propose a way to optimize the geometry code without sacrificing too much in the connectivity code. In our approach, we achieve approximately two bits/triangle for the connectivity before entropy coding, which is not as good as other published algorithms but certainly not significantly worse. Our approach is based on the parallelogram prediction method for mesh geometry. This method is based on the observation that two adjacent triangles in a typical mesh tend to form a shape similar to a parallelogram. If an algorithm uses a parallelogram prediction method then it should build a traversal structure of triangles covering all vertices. The vertex coordinates are then predicted as the structure is traversed. The cost of this code is then the entropy of the distribution of the vertex prediction errors. Since this entropy is hard to manipulate, the accepted practice is to measure the code's effectiveness in the approximation sense, i.e. as the sum of the lengths of the vertex prediction error vectors. The full version of this paper is available at .
Generalized local interactions in 1D: solutions of quantum many-body systems describing distinguishable particles

As is well known, there exists a four-parameter family of local interactions in 1D. We interpret these parameters as coupling constants of delta-type interactions which include different kinds of momentum-dependent terms, and determine all cases leading to many-body systems of distinguishable particles which are exactly solvable by the coordinate Bethe ansatz. We find two such families of systems, one with two independent coupling constants deforming the well-known delta-interaction model to non-identical particles, and the other with a particular one-parameter combination of the delta and (the so-called) delta-prime interaction. We also find that the model of non-identical particles gives rise to a somewhat unusual solution of the Yang–Baxter relations. For the other model we write down explicit formulae for all eigenfunctions.
Consumer effects on ecosystem functioning in rock pools: roles of species richness and composition

A key challenge in research linking biodiversity and ecosystem functioning is to incorporate the trophic interactions that characterise natural systems. There is a particular shortage of studies investigating consumer species richness and composition (identity) effects in the context of ecosystem development (or succession). We manipulated the richness and composition of an assemblage of molluscan grazers (Patella ulyssiponensis, Gibbula umbilicalis and Littorina littorea) added to rock pools denuded of existing biota. We created monocultures and all possible multispecies combinations in a substitutive design, and ran a field experiment for 13 mo. We used 2 separate nested analyses to isolate the roles of species richness, species composition nested within levels of species richness and the specific effect of the limpet P. ulyssiponensis, a putative key species. We found no evidence that the biomass or productivity of the developing macroalgal assemblage was affected by grazer richness or species composition nested within richness levels. Rather, the presence of P. ulyssiponensis, irrespective of the presence of other grazer species, acted to suppress mean values of these response variables. Biomass and productivity were not strongly related, showing that they provide unique information on ecosystem functioning in this system. Macroalgal species richness was also reduced by P. ulyssiponensis, and correlated positively with macroalgal biomass, indicating a link between these response variables. Macroalgal species composition was largely insensitive to either species richness or the presence of P. ulyssiponensis, but responded to particular combinations of species within levels of these factors. The key role of P. ulyssiponensis in determining ecosystem functioning is apparent from our results, but we note that consumer species richness may play an important role under more heterogeneous conditions.
Can Exchange Traded Funds be Used to Exploit Country and Industry Momentum?

There is overwhelming empirical evidence on the existence of country and industry momentum effects. This line of research suggests that investors who buy countries and industries with relatively high past returns and sell countries and industries with relatively low past returns will earn positive risk-adjusted returns. These studies focus on country and industry indexes that cannot be traded directly by investors. This warrants the question whether country and industry momentum effects can really be exploited by investors or are illusionary in nature because they exist only on non-tradable assets. We analyze the profitability of country and industry momentum strategies using actual price data on Exchange Traded Funds (ETFs). We find that, over the sample periods that these ETFs were traded, an investor would have been able to exploit country and industry momentum strategies with an excess return of about 5% per annum. These returns cannot be explained by unconditional exposures to the Fama-French factors. The daily average bid-ask spreads on ETFs are substantially below the implied break-even transaction costs levels. Hence, we conclude that investors that are not willing or able to trade individual stocks may use ETFs to benefit from momentum effects in country and industry portfolios.
Exploring Personality as a Predictor of Academic Factors and Mental Health Among Veterinary Students at the Ontario Veterinary College

Exploring Personality as a Predictor of Academic Factors and Mental Health Among Veterinary Students at the Ontario Veterinary College Monika Lauron Goetz University of Guelph, 2017 Advisors: Dr. Andria Jones-Bitton Dr. Peter Conlon Veterinary students and veterinary professionals are at high risk for mental health issues such as depression. This thesis explores associations of personality with mental health outcomes in veterinary students for the first time. Myers-Briggs Type Indicator (MBTI) personality data were collected for eleven graduating classes of veterinary students at the Ontario Veterinary College (OVC), and mental health data were collected for one. OVC veterinary students were diverse in their MBTI distribution. Significant associations were identified between the MBTI and gender, career interests, and academic performance. Associations between the MBTI and perceived learning climate and stressors were explored. Students of the Introversion and Intuition preferences had greater odds of scoring above the research threshold for depression and scored lower on psychological capital than their opposite preferences. These associations warrant further investigation to understand the impact that personality and mental health may have on veterinary students and their academic experiences.
The inter-individual relationship between training status and activity pattern during small-sided and full-sized games in professional male football players

ABSTRACT Objectives: We analysed the inter-individual relationship between training status and activity pattern in small-sided games (SSG) and full-sized games (FG). Methods: Fourteen Italian elite male senior football players were monitored during four training sessions incorporating SSG, and six FG, during the pre-season. Baseline measurements included, countermovement jump (CMJ), 5-m sprint time and Yo-Yo intermittent recovery test level 1 distance (YYIR1). Activity pattern was collected via 15-Hz global positioning system with 100-Hz accelerometer integrated. Results: Maximum accelerations (Accmax) and maximum decelerations (Decmax) showed moderate correlations (P < 0.05; r = 0.49 and 0.52) between SSG and FG. YYIR1 correlated with total distance covered (TD) in both SSG and FG (P < 0.05; r = 0.42 to 0.57) and with high-intensity distance (HIR) during FG (P < 0.05; r = 0.46 ± 0.38). CMJ showed positive correlations with TD, Accmax, Decmax, total accelerations (Acctot) and total decelerations (Dectot) during FG (P < 0.05; r = 0.40 ± 0.38, 0.41 ± 0.40, 0.46 ± 0.38, 0.65 ± 0.29, 0.57 ± 0.33). Multiple regression analysis revealed Decmax during SSG, as significant predictor of physical performance during FG, explaining a significant amount of variation in HIR, very-high speed running, Accmax and Decmax (P < 0.05; R2 = 0.49, 0.44, 0.26 and 0.49) during FG. Conclusions: SSG seems more effective to enhance muscular efforts occurring during FG, such as accelerations and decelerations, rather than speed patterns. Specifically, Decmax distance imposed during SSG was identified as the predictor of players’ movement patterns during FG. Thus, importance of eccentric strength (i.e. imposed when decelerating) to achieve football-specific fitness is emphasised. These findings may assist coaches and any football practitioners for pre-season programming.
Data Literacy for Social Studies: Examining the Role of Data Visualizations in K–12 Textbooks

Abstract The rising prevalence of data visualizations in the political and economic spheres requires an increasingly data literate population. Data are used to persuade people how to vote, support policies, adopt arguments or agendas, and buy products. Furthermore, data literacy is a specialized literacy skill that students need to employ to make meaning within the academic disciplines. This article presents a study of over 3,000 data visualizations in 42 K–12 social studies textbooks, addressing the questions: How prevalent are data visualizations in social studies texts? How are data visually represented in social studies texts? What purpose do data visualizations serve in social studies texts? and To what degree do social studies texts support and encourage analysis of data visualizations? Findings reveal not only the important role that data visualizations play in communicating information within social studies materials but also implications for social studies research and instruction.
Is Trump always rambling like a fourth-grade student? An analysis of stylistic features of Donald Trump’s political discourse during the 2016 election

During the 2016 election, Donald Trump was characterized by his simple, pompous and repetitive language. However, studies have shown that sometimes he does not speak the way he used to. Critical discourse analysis suggests that political discourse analysis should include both the characterization of the text and the systematic description of the context. Thus, this study intends to evaluate stylistic features of Donald Trump’s political discourse based on the evolution over time as well as the genre variation by employing a comparison between Obama, Clinton and Trump. Results show that in debates, Trump uses less diverse vocabulary and simpler sentences. In campaign speeches, nonetheless, along with the change of circumstances, he sometimes employed a richer vocabulary and well-edited sentences. In addition, Trump’s speeches contain relatively more central themes in his campaign speeches. His concentration on political themes may meet key interests of a large proportion of electorates.
Personal Knowledge Management: a Study of Knowledge Behaviour of Academicians

Current theories of knowledge management postulate a cycle of knowledge creation, refinement and implementation that hinges on the transformation of tacit, or practical, into explicit, or discursive, knowledge. The modern organisation, because it is characterised by diverse local practices, and by the increasing salience of professional work, is thus a complex mosaic of situated knowledge, grounded in process. Enabling organisations to capture, share and apply the situated knowledge grounded in the process is seen as fundamental to competing in the knowledge economy. The study is focussed on the various knowledge activities of faculty members to understand the extent of impact of information systems on those activities and how those activities contribute to value creation and knowledge management. The results of this study suggest the presence of certain type of knowledge behaviours which facilitate knowledge management.
On the Detection of High-Impact Refactoring Opportunities in Programs

We present a novel approach to detect refactoring opportunities by measuring the participation of references between types in instances of patterns representing design flaws. This technique is validated using an experiment where we analyse a set of 95 open-source Java programs for instances of four patterns representing modularisation problems. It turns out that our algorithm can detect high impact refactorings opportunities - a small number of references such that the removal of those references removes the majority of patterns from the program.
A Survey of Biometric Gait Recognition: Approaches, Security and Challenges

Biometric systems are becoming increasingly important, since they provide more reliable and efficient means of identity verification. Biometric gait recognition (i.e. recognizing people from the way they walk) is one of the recent attractive topics in biometric research. This paper presents biometric user recognition based on gait. Biometric gait recognition is categorized into three groups based on: machine vision, floor sensor and wearable sensor. An overview of each gait recognition category is presented. In addition, factors that may influence gait recognition are outlined. Furthermore, the security evaluations of biometric gait under various attack scenarios are also presented.
Natural Strain Variation and Antibody Neutralization of Dengue Serotype 3 Viruses

Dengue viruses (DENVs) are emerging, mosquito-borne flaviviruses which cause dengue fever and dengue hemorrhagic fever. The DENV complex consists of 4 serotypes designated DENV1-DENV4. Following natural infection with DENV, individuals develop serotype specific, neutralizing antibody responses. Monoclonal antibodies (MAbs) have been used to map neutralizing epitopes on dengue and other flaviviruses. Most serotype-specific, neutralizing MAbs bind to the lateral ridge of domain III of E protein (EDIII). It has been widely assumed that the EDIII lateral ridge epitope is conserved within each DENV serotype and a good target for vaccines. Using phylogenetic methods, we compared the amino acid sequence of 175 E proteins representing the different genotypes of DENV3 and identified a panel of surface exposed amino acids, including residues in EDIII, that are highly variant across the four DENV3 genotypes. The variable amino acids include six residues at the lateral ridge of EDIII. We used a panel of DENV3 mouse MAbs to assess the functional significance of naturally occurring amino acid variation. From the panel of antibodies, we identified three neutralizing MAbs that bound to EDIII of DENV3. Recombinant proteins and naturally occurring variant viruses were used to map the binding sites of the three MAbs. The three MAbs bound to overlapping but distinct epitopes on EDIII. Our empirical studies clearly demonstrate that the antibody binding and neutralization capacity of two MAbs was strongly influenced by naturally occurring mutations in DENV3. Our data demonstrate that the lateral ridge “type specific” epitope is not conserved between strains of DENV3. This variability should be considered when designing and evaluating DENV vaccines, especially those targeting EDIII.
Extroversion Personality, Domain Knowledge, and the Creativity of New Product Development Engineers

Creativity refers to a person’s thinking of new and useful ideas at work. Drawing on the personality literature, this study proposes that employees with high extroversion personality will exchange job relevant information with colleagues to generate creativity. Drawing on the information exchange theory, this study further proposes that the effect of extroversion personality with creativity via information exchange will be stronger for workers with insufficient domain knowledge. Data collected from Taiwanese new product development engineers support our hypotheses. Previous research found that extroverted persons perform more creatively because they are more confident in their abilities. This study further demonstrates that, after controlling for self-efficacy, extroverted engineers can still think of creative ideas via exchanging information with colleagues. Although domain knowledge has been shown as crucial to creativity, few studies have explored how to stimulate creative ideas from workers with insufficient domain knowledge. This study demonstrates a useful substitute for domain knowledge, namely the extroversion personality, which may inspire creativity via exchanging information with colleagues.
Dynamic transparent virtual network embedding over elastic optical infrastructures

We propose a novel dynamic transparent virtual network embedding (VNE) algorithm, which considers node mapping and link mapping jointly, for network virtualization over optical orthogonal frequency-division multiplexing (O-OFDM) based elastic optical infrastructures. For each virtual optical network (VON) request, the algorithm first transfers the substrate optical network into a layered-auxiliary-graph according to the spectrum usage of each fiber link, then applies a node mapping approach that considers the local information of all substrate nodes, and accomplishes the link mapping, in a single layer of the auxiliary graph. The simulation results verify that the proposed algorithm considers the uniqueness of O-OFDM networks and outperforms two reference algorithms that directly apply the VNE schemes developed for Layer 2/3 or WDM network virtualization, by providing lower VON blocking probability. The simulations with a realistic topology also demonstrate that the average lengths of embedded substrate paths are well-controlled within the typical transmission reaches of O-OFDM signals. To the best of our knowledge, this is the first proposal that includes both link mapping and node mapping to address dynamic transparent VNE over elastic optical infrastructures.