Miracle-dz/UniFAR-FTUs huggingface dataset:
Age-Related Subgingival Colonization of Aggregatibacter actinomycetemcomitans, Porphyromonas gingivalis and Parvimonas micra—A Pragmatic Microbiological Retrospective Report

The aim of this study was to compare data about the prevalence and proportions of the bacterial species Aggregatibacter actinomycetemcomitans, Porphyromonas gingivalis, and Parvimonas micra in periodontitis pocket samples collected from young, <35 years, and old, >35-year-old patients, YP and OP, respectively. The results from the analyses of a total of 3447 subgingival plaque samples analyzed for clinical diagnosis purposes by cultivation regarding the proportions of these species were collected from a database and elucidated. The prevalence of A. actinomycetemcomitans was found to be more than twice as high (OR = 2.96, 95% CI; 2.50–3.50) in samples from the younger (42.2%) than the older group (20.4%) (p < 0.001). The prevalence of P. micra was significantly lower in samples from the younger age group (OR = 0.43, 95%) (p < 0.001), whereas P. gingivalis was similarly distributed (OR = 0.78, 95%) in the two age groups (p = 0.006). A similar pattern was noticed for A. actinomycetemcomitans and P. gingivalis when high proportions (>50%) of the samples of these bacterial species were elucidated. In contrast, the proportion of samples containing >50% with P. micra was lower compared with the two other bacterial species. Furthermore, it was noted that the proportion of samples from old patients containing A. actinomycetemcomitans in combination with P. micra was almost three times higher than in samples when P. micra was replaced by P. gingivalis. In conclusion, A. actinomycetemcomitans showed an increased presence and proportion in samples from young patients compared with the old patients, while P. gingivalis was similarly distributed in the two age groups. P. micra showed an increased presence and proportion in samples from old patients compared with the young patients.
Quantum Interferences in the Dynamics of Atoms and Molecules in Electromagnetic Fields

Quantum interference, coherent superposition of quantum states, are widely used for the understanding and engineering of the quantum world. In this thesis, two distinct problems that are rooted in quantum interference are discussed with their potential applications: 1. Laser induced electron diffraction (LIED) and molecular orbital imaging, 2. Collective effects in dense vapors and dipole induced electromagnetic transparency (DIET). The first part deals with the recollision mechanism in molecules when the system is exposed to high intensity infrared laser fields. The interaction with the intense field will tunnel ionize the system, creating an electron wave packet in the continuum. This wave packet follows an oscillatory trajectory driven by the laser field. This results in a collision with the parent ion from which the wave packet was formed. This scattering process can end up in different channels including either inelastic scattering resulting in high harmonic generation (HHG) and non-sequential double ionization, or elastic scattering often called laser induced electron diffraction. LIED carries information about the molecule and about the initial state from which the electron was born as diffraction patterns formed due to the interference between different diffraction pathways. In this project, a method is developed for imaging molecular orbitals relying on scattered photoelectron spectra obtained via LIED. It is based on the fact that the scattering wave function keeps the memory of the object from which it has been scattered. An analytical model based on the strong field approximation (SFA) is developed for linear molecules and applied to the HOMO and HOMO-1 molecular orbitals of carbon dioxide. Extraction of orbital information imprinted in the photoelectron spectra is presented in detail. It is anticipated that it could be extended to image the electro-nuclear dynamics of such systems. The second part of the thesis deals with collective effects in dense atomic or molecular vapors. The action of light on the vapor samples creates dipoles which oscillate and produce secondary electro-magnetic waves. When the constituent particles are close enough and exposed to a common exciting field, the induced dipoles can affect one another, setting up a correlation which forbids them from responding independently towards the external field. The result is a cooperative response leading to effects unique to such systems which include Dicke narrowing, superradiance, Lorentz-Lorenz and Lamb shifts. To this list of collective effects, one more candidate has been added, which is revealed during this study: an induced transparency in the sample. This transparency, induced by dipole-dipole interactions, is named “dipole-induced electromagnetic transparency”. The collective nature of the dense vapor excitation reduces the group velocity of the transmitted light to a few tens of meter per second resulting in 'slow' light. These effects are demonstrated for the D1 transitions of 85Rb and other potential applications are also discussed.
Unified categorical models for three typical resource allocation problems

This paper concerns formalization of resource allocation using category theory, rather than a new algorithm to solve these problems. The unified and efficient categorical models for three specific resource allocation problems-including dinning philosophers problem, drinking philosophers problem and committee coordination problem - is originally presented based on Chandy-Misra’s acyclic precedence graph strategy and our previous experience in defining the categorical semantics for distributed dinning philosophers problem. Four categories (including Dinners Category, Drinkers Category, Committees Category and Functors Category) defined in our paper not only facilitate to formalize usual concepts (such as task, resource, precedence) of resource allocation problems, but also give good directions to reason the relationships between these three typical problems. Finally, we formally proof some properties of symmetry, safety (non-deadlock), liveness (non-starvation) and concurrency, which all satisfied in our models.
The Asymptotic Behavior of the Term Structure of Interest Rates

In this dissertation we investigate long-term interest rates, i.e. interest rates with maturity going to infinity, in the post-crisis interest rate market. Three different concepts of long-term interest rates are considered for this purpose: the long-term yield, the long-term simple rate, and the long-term swap rate. We analyze the properties as well as the interrelations of these long-term interest rates. In particular, we study the asymptotic behavior of the term structure of interest rates in some specific models. First, we compute the three long-term interest rates in the HJM framework with different stochastic drivers, namely Brownian motions, Levy processes, and affine processes on the state space of positive semidefinite symmetric matrices. The HJM setting presents the advantage that the entire yield curve can be modeled directly. Furthermore, by considering increasingly more general classes of drivers, we were able to take into account the impact of different risk factors and their dependence structure on the long end of the yield curve. Finally, we study the long-term interest rates and especially the long-term swap rate in the Flesaker-Hughston model and the linear-rational methodology.
Loader: A Log Anomaly Detector Based on Transformer

Detecting anomalies in logs is crucial for service and system management, since logs are widely used to record the runtime status, and are often the only data available for postmortem analysis. Since anomalies are usually rare in real-world services and systems, a common and feasible practice is to mine or learn normal patterns from logs, and deem those violating the normal patterns as anomalies. As log sequences are a kind of time series data, RNN (Recurrent Neural Network) and its variants have been extensively employed to capture the normal patterns. Nevertheless, the sequential nature of RNN and its variants makes them hard to parallelize and capture long-term dependencies, which may hinder their performance. To address this issue, in this paper we propose Loader, a novel semi-supervised <underline><bold>lo</bold></underline>g <underline><bold>a</bold></underline>nomaly <underline><bold>d</bold></underline>etector based on Transform<underline><bold>er</bold></underline>, because the Transformer architecture eschews recurrence and is able to draw global dependencies. Loader leverages the Transformer encoder to capture normal patterns from normal log sequences. When detecting, it gives a set of candidate log templates, that may appear after the input log substring under normal conditions. If the template of the actual next log message is not within the candidate set, this implies an anomaly. Previous similar methods select the most possible <inline-formula><tex-math notation="LaTeX">$k$</tex-math><alternatives><mml:math><mml:mi>k</mml:mi></mml:math><inline-graphic xlink:href="quan-ieq1-3280575.gif"/></alternatives></inline-formula> log templates as candidates in any case, so the performance is sensitive to <inline-formula><tex-math notation="LaTeX">$k$</tex-math><alternatives><mml:math><mml:mi>k</mml:mi></mml:math><inline-graphic xlink:href="quan-ieq2-3280575.gif"/></alternatives></inline-formula>, and it is nontrivial to pick a proper <inline-formula><tex-math notation="LaTeX">$k$</tex-math><alternatives><mml:math><mml:mi>k</mml:mi></mml:math><inline-graphic xlink:href="quan-ieq3-3280575.gif"/></alternatives></inline-formula>. To alleviate this, we design a more flexible and robust ‘top-<inline-formula><tex-math notation="LaTeX">$p$</tex-math><alternatives><mml:math><mml:mi>p</mml:mi></mml:math><inline-graphic xlink:href="quan-ieq4-3280575.gif"/></alternatives></inline-formula>’ algorithm, which determines the candidate set based on the cumulative probability of the most possible log templates. Extensive experiments are conducted based on three public log datasets, the experimental results validate the effectiveness and competitiveness of our approach.
Compressor cascade positive and negative stall incidence angle correlation modelling using artificial neural networks

: The analysis of the flows by computational fluid dynamics becomes useful design and optimization method during recent years. Despite the advances in the computational power but it could be still very demanding. Therefore empirical models are commonly used as a main tool for design and prediction of basic performance of axial compressor cascades. The empirical correlations are derived from experimental data obtained from two-dimensional measurements. Unfortunately, sufficient amount of data is available only in cases of well-known airfoils as e
On the Equivalence Between SOVA and - -MAP Decodings

In this letter, it is shown that after a proper simple modification, the soft-output Viterbi algorithm (SOVA) proposed by Hagenauer and Hoeher becomes equivalent to the - -maximum a posteriori (MAP) decoding algorithm. Consequently, this modified SOVA allows to implement the - -MAP decoding algorithm by simply adjusting the conventional Viterbi algorithm. Hence, it provides an attractive solution to achieve low-complexity near-optimum soft-input soft-output decoding.
A Novel Compact Broadband SIW Six-Port Junction for Angle-of-Arrival Applications

A compact broadband substrate integrated waveguide (SIW) six-port junction based on a novel topology and its application in angle-of-arrival (AoA) finding system are proposed in this article. The miniaturization design philosophy of the six-port junction is based on the change of the conventional topology rather than the special structure of the discrete component or the advantage of the fabrication technology. The proposed six-port junction is constructed by two multistep <inline-formula> <tex-math notation="LaTeX">$H$ </tex-math></inline-formula>-plane Hybrid couplers, one complementary split-ring resonator (CSRR) loaded wideband 90° phase shifter, two power dividers, and two extra phase shifters of arbitrary phase. The additional phase differences introduced by the extra phase shifters do not deteriorate the application performance based on the <inline-formula> <tex-math notation="LaTeX">$S$ </tex-math></inline-formula>-parameters requirement of the six-port junction design. The power divider and the adjacent extra phase shifter are realized by one <inline-formula> <tex-math notation="LaTeX">$E$ </tex-math></inline-formula>-plane 3-dB coupler (3dB-C) with one port short by metalized holes. The combination of <inline-formula> <tex-math notation="LaTeX">$E$ </tex-math></inline-formula>- and <inline-formula> <tex-math notation="LaTeX">$H$ </tex-math></inline-formula>-plane coupler significantly reduces the volume of the entire six-port junction. The fabrication of the prototype is measured by a commercial vector network analyzer and shows a good agreement with the simulation results. The fractional working bandwidth is 32.2% at 7.15 GHz and more than 20% volume is reduced compared with other designs with comparable bandwidth. Besides, to directly verify the availability of the novel topology, a simplified six-port AoA finding system utilized the proposed six-port junction is realized. The maximum average error of the measured incident angle in the entire bandwidth is no larger than 1.65°, which is comparable to the traditional system. However, it is worth to be noted that the proposed structure can make a considerable reduction of volume and can be utilized widely for the miniaturization design of the six-port measurement systems.
Predictors of Recovery Following Lumbar Microdiscectomy for Sciatica: A Systematic Review and Meta-Analysis of Observational Studies

Chronic post-surgical pain is reported by up to 40% of patients after lumbar microdiscectomy for sciatica, a complaint associated with disability and loss of productivity. We conducted a systematic review of observational studies to explore factors associated with persistent leg pain and impairments after microdiscectomy for sciatica. We searched eligible studies in MEDLINE, Embase, and CINAHL that explored, in an adjusted model, predictors of persistent leg pain, physical impairment, or failure to return to work after microdiscectomy for sciatica. When possible, we pooled estimates of association using random-effects models using the Grading of Recommendations Assessment, Development, and Evaluation approach. Moderate-certainty evidence showed that the female sex probably has a small association with persistent post-surgical leg pain (odds ratio (OR) = 1.15, 95% confidence interval (CI) = 0.63 to 2.08; absolute risk increase (ARI) = 1.8%, 95% CI = -4.7% to 11.3%), large association with failure to return to work (OR = 2.79, 95% CI = 1.27 to 6.17; ARI = 10.6%, 95% CI = 1.8% to 25.2%), and older age is probably associated with greater postoperative disability (β = 1.47 points on the 100-point Oswestry Disability Index for every 10-year increase from age (>/=18 years), 95% CI = -4.14 to 7.28). Among factors that were not possible to pool, two factors showed promise for future study, namely, legal representation and preoperative opioid use, which showed large associations with worse outcomes after surgery. The moderate-certainty evidence showed female sex is probably associated with persistent leg pain and failure to return to work and that older age is probably associated with greater post-surgical impairment after a microdiscectomy. Future research should explore the association between legal representation and preoperative opioid use with persistent pain and impairment after microdiscectomy for sciatica.
The Quality of Life of Adolescents Experiencing Online Game Addiction During the COVID-19 Pandemic

The availability of the internet and the increase in stress in adolescents caused by the pandemic have led adolescents to frequently seek entertainment through online games. Online gaming can negatively impact adolescents by causing a decline in their physical health, psychological issues, difficulty forming healthy social relationships, and decline their quality of life. This study identified the relationship between online game addiction and the quality of life of adolescents during the COVID-19 pandemic. This research utilized a cross-sectional approach and involved 96 adolescents as the research sample selected using the incidental sampling method. Data collection was carried out using the Game Addiction Scale for Adolescent and WHOQOL-Bref, while the Spearman Rho test was used for data analysis. The results of the data analysis showed a significance p-value of 0.000 (p < 0.05) and r = -0.711, indicating that there was a unidirectional relationship between online game addiction and quality of life. Thus, it can be concluded that the higher the level of online game addiction, the lower the quality of life of adolescents. Abstrak Kualitas Hidup Remaja yang Mengalami Kecanduan Game Online Selama Pandemi COVID-19. Ketersediaan internet dan meningkatnya stres remaja akibat pandemi membuat remaja sering mencari hiburan melalui game online. Bermain game online secara berlebihan dapat menyebabkan mereka mengalami kecanduan. Hal tersebut dapat menimbulkan dampak negatif seperti penurunan kesehatan fisik, masalah psikologis, hubungan sosial dan penurunan kualitas hidup mereka. Penelitian ini bertujuan untuk mengidentifikasi hubungan antara kecanduan game online dengan kualitas hidup remaja selama pandemi COVID-19. Penelitian ini menggunakan pendekatan cross-sectional dan memilih 96 remaja sebagai sampel penelitian yang dipilih dengan metode incidental sampling. Pengumpulan data dilakukan dengan menggunakan Game Addiction Scale for Adolescent dan WHOQOL-Bref, sedangkan analisis data menggunakan uji Spearman Rho. Hasil analisis data menunjukkan signifikansi nilai p sebesar 0,000 (p < 0,05) dan r = -0,711, menunjukkan bahwa terdapat hubungan searah antara kecanduan game online dengan kualitas hidup. Dengan demikian, dapat disimpulkan bahwa semakin tinggi tingkat kecanduan game online maka kualitas hidup remaja akan semakin rendah. Kata Kunci: game online, kecanduan, kualitas hidup, remaja
Economic growth, climate change, and agriculture sector: ARDL bounds testing approach for Bangladesh (1971-2020)

Agriculture, Food security, Climate change, and food import are vital components of an economy. This article empirically explored the long-run and short-run impact of these variables on the economic development of Bangladesh by employing the ARDL model over the period from 1971 to 2020. The outcome of the F-bounds test confirmed the existence of a no long-run relationship among the variables examined, and hence, the appropriate model is ARDL. The study then analysed the short-run impact of agriculture, food security, food import and climate change on economic growth. The short-run and long-run coefficients revealed a positive and significant impact of the agriculture sectors on economic growth in Bangladesh in the short-run and long-run. Findings further showed that climate change and food security have a positive and insignificant impact on economic development. Food import has a negative and insignificant impact on economic growth in the short-run and an insignificant positive impact in the long-run+. Therefore, the study concludes that Bangladesh should invest in the agriculture sector as an engine of economic growth. Climate change, food security and food imports are essential for Bangladesh's economy.
DGM-VINS: Visual–Inertial SLAM for Complex Dynamic Environments With Joint Geometry Feature Extraction and Multiple Object Tracking

Most current state-of-the-art simultaneous localization and mapping (SLAM) algorithms perform well in static environments. However, their applications in real-world scenarios are limited by the assumption that environments are static because their performance becomes unstable in complex dynamic environments. To enhance system stability and localization accuracy in complex dynamic scenes, this article presents a novel visual–inertial SLAM system called DGM-VINS. In DGM-VINS, a joint geometric dynamic feature extraction module (JGDFE) is designed, which can combine the advantages of multiple geometric constraints and effectively reduce the limitations of a single geometric constraint in the application process. In addition, a temporal instance segmentation module (TISM) is presented to establish the temporal correlation of instance objects in consecutive frames, which effectively addresses the instance segmentation issue in complex environments. The inertial measurement unit (IMU) is utilized for motion prediction and consistency detection to improve localization accuracy in challenging environments with weak textures. The proposed methodology is tested in various public datasets and actual scenarios, and the results demonstrate superior accuracy and robustness to existing methods in complex dynamic scenarios.
The Superposition Principle: A Conceptual Perspective on Pedestrian Stream Simulations

Models using a superposition of scalar fields for navigation are prevalent in microscopic pedestrian stream simulations. However, classifications, differences, and similarities of models are not clear at the conceptual level of navigation mechanisms. In this paper, we describe the superposition of scalar fields as an approach to microscopic crowd modelling and corresponding motion schemes. We use this background discussion to focus on the similarities and differences of models, and find that many models make use of similar mechanisms for the navigation of virtual agents. In some cases, the differences between models can be reduced to differences between discretisation schemes. The interpretation of scalar fields varies across models, but most of the time this variation does not have a large impact on simulation outcomes. The conceptual analysis of different models of pedestrian dynamics allows for a better understanding of their capabilities and limitations and may lead to better model development and validation.
Multimodal Solution for a Circular Waveguide Radiating Into Multilayered Structures Using the Axially Symmetric Modes

In this article, an exact formulation is derived for the mode reflection coefficient (and in general, the full S-parameter matrix) for a circular waveguide radiating into a multilayered structure and when excited with any combination of axially symmetric modes (i.e., modes of the form TE0m and TM0m, where $\mathbf {m}$ is a positive integer). This formulation solves for the fields in the waveguide, including fields resulting from higher-order evanescent modes, using Fourier analysis. This leads to an accurate calculation of the mode S-parameter matrix, which includes the reflection coefficient of each excited mode. The derived formulations were validated through comparison to those computed using full-wave 3-D electromagnetic simulations. Additional simulations demonstrated the effect of considering higher-order modes on the results. The effect of having a finite flange and sample size on the complex reflection coefficient was also shown through 3-D simulations, indicating the relative insensitivity of the TE01 probe to edge effects. Reflection coefficient measurements, using a circular waveguide probe with the TE01 mode, were performed to experimentally verify the accuracy of the formulations. Forward-iterative optimization (i.e., optimal curve fitting) techniques were then performed on the reflection coefficient measurements to demonstrate the efficacy of this method for accurately estimating the thickness and complex permittivity of thin dielectric layers.