Miracle-dz/UniFAR-FTUs huggingface dataset:
Impact of Selective median filter on dental caries classification system using deep learning models

Accurate classification of dental caries is crucial for effective oral healthcare. Filters help to increase exposure of the picture taken for the investigation without degrading image quality. Selective median filter is the chosen preprocessing technique that helps to reduce the noise present in the captured image. Dental caries classification system is a model used to detect the presence of cavity in the given input image. Dental caries classification system is evolved with the use of conventional techniques to artificial neural network. Deep learning models are the artificial neural network models that can able to learn the features from the raw images available in the dataset. If this raw image has noise, then it severely affects the accuracy of the deep learning models. In this paper, impact of the preprocessing technique on the classification accuracy is analyzed. Initially, raw images are taken for training on deep learning models without applying any preprocessing technique. This study investigates the impact of Selective median filtering on a dental caries classification system using deep learning models. The motivation behind this research is to enhance the accuracy and reliability of dental caries diagnosis by reducing noise, removing artifacts, and preserving important details in dental radiographs. Experimental results demonstrate that the implementation of Selective median filtering significantly improves the performance of the deep learning model. The hybrid neural network (HNN) classifier achieves an accuracy of 96.15% with Selective median filtering, outperforming the accuracy of 85.07% without preprocessing. The study highlights the theoretical contribution of Selective median filtering in enhancing dental caries classification systems and emphasizes the practical implications for dental clinics, offering improved diagnostic capabilities and better patient outcomes.
Two Models of Coagulation With Instantaneous Gelation

Author(s): Bechor, Elan J. | Advisor(s): Rezakhanlou, Fraydoun | Abstract: Two models of coagulation are presented: one, a system of coupled partial differential equations and the other microscopic Brownian particles. Both models feature a parameter that represents the tendency of two particles to coagulate at sufficiently close distances. Both models have a phase transition, viewed as the mass clumping together as a gel. Previous work has shown the models are connected, and in here we show that their phase transition to instantaneous gelation is connected as well.
Position estimation of a gamma-ray source using NaI-plastic combined detectors

In this paper, a detector was specifically designed for obtaining directional information of incident gamma-rays. The detector consisted of two NaI(Tl)-plastic combined scintillators, each one coupled to a PMT. We considered the heights of the photopeaks of the NaI(Tl) scintillators and Compton maxima of the plastic scintillators, observed in the recorded gamma spectra, to determine the direction of the gamma-rays. Overall, a detector with such a capability is useful in various fields, namely radiation monitoring and astronomy.
Downside Risk Aplicado a Carteiras de Ações Brasileiras Durante Período Pandêmico da COVID-19

Objective of this paper is the formation and optimization of investment port-folios with shares traded on B3 and based on the theory of diversification of the Markowitz model and on Quadratic Programming. The minimization of the portfolio risk was considered by the Downside Risk system, modeled and implemented computationally. The data collection period began in 2020, the year in which there was a global economic crisis due to the Sars-CoV-2 pandemic and consequent isolation measures that profoundly affected the economy. Three portfolios were formed that performed between January 2021 and March 2022 and showed better-than-expected results compared to the percentage change in the Ibovespa.
TENSE SELECTION AND THE TEMPORAL INTERPRETATION OF COMPLEMENT CLAUSES

The problem addressed in this paper is tense selection. Clausal complements of verbs such as expect and predict appear to select for finite verbs that are future marked and for infinitival complements that have a future interpretation. It is argued that these two facts can (and must) be given a uniform account. To that end I adopt a relational treatment of tenses and argue for a particular architecture of composition in which the free application of abstraction is component of the grammar. The lexical semantics of future-selecting verbs is argued to contain an implicit future operator and these verbs are taken to select for future relations. The resulting framework is one in which untensed clauses are fundamentally distinguished from tensed clauses, and typeshifting is a regular part of the interpretive process.
Glaucoma-Associated CDR1 Peptide Promotes RGC Survival in Retinal Explants through Molecular Interaction with Acidic Leucine Rich Nuclear Phosphoprotein 32A (ANP32A)

Glaucoma is a complex, multifactorial optic neuropathy mainly characterized by the progressive loss of retinal ganglion cells (RGCs) and their axons, resulting in a decline of visual function. The pathogenic molecular mechanism of glaucoma is still not well understood, and therapeutic strategies specifically addressing the neurodegenerative component of this ocular disease are urgently needed. Novel immunotherapeutics might overcome this problem by targeting specific molecular structures in the retina and providing direct neuroprotection via different modes of action. Within the scope of this research, the present study showed for the first time beneficial effects of the synthetic CDR1 peptide SCTGTSSDVGGYNYVSWYQ on the viability of RGCs ex vivo in a concentration-dependent manner compared to untreated control explants (CTRL, 50 µg/mL: p < 0.05 and 100 µg/mL: p < 0.001). Thereby, this specific peptide was identified first as a potential biomarker candidate in the serum of glaucoma patients and was significantly lower expressed in systemic IgG molecules compared to healthy control subjects. Furthermore, MS-based co-immunoprecipitation experiments confirmed the specific interaction of synthetic CDR1 with retinal acidic leucine-rich nuclear phosphoprotein 32A (ANP32A; p < 0.001 and log2 fold change > 3), which is a highly expressed protein in neurological tissues with multifactorial biological functions. In silico binding prediction analysis revealed the N-terminal leucine-rich repeat (LRR) domain of ANP32A as a significant binding site for synthetic CDR1, which was previously reported as an important docking site for protein-protein interactions (PPI). In accordance with these findings, quantitative proteomic analysis of the retinae ± CDR1 treatment resulted in the identification of 25 protein markers, which were significantly differentially distributed between both experimental groups (CTRL and CDR1, p < 0.05). Particularly, acetyl-CoA biosynthesis I-related enzymes (e.g., DLAT and PDHA1), as well as cytoskeleton-regulating proteins (e.g., MSN), were highly expressed by synthetic CDR1 treatment in the retina; on the contrary, direct ANP32A-interacting proteins (e.g., NME1 and PPP2R4), as well as neurodegenerative-related markers (e.g., CEND1), were identified with significant lower abundancy in the CDR1-treated retinae compared to CTRL. Furthermore, retinal protein phosphorylation and histone acetylation were also affected by synthetic CDR1, which are both partially controlled by ANP32A. In conclusion, the synthetic CDR1 peptide provides a great translational potential for the treatment of glaucoma in the future by eliciting its neuroprotective mechanism via specific interaction with ANP32A’s N terminal LRR domain.
Competing Three-Dimensional Mechanisms in Compressor Flows

The authors would like to thank Rolls-Royce plc for their contributions and permission to publish this work, Chris Hall, Ian Bousfield, Simon Gallimore and Nicholas Cumpsty for their invaluable advice, the EPSRC for their support, TURBOSTREAM for the use of their solver, and Graham Pullan for his comments on 3D thinking.
Speech adaptation to palatal perturbation: Evidence for sensorimotor reorganization across the workspace

It has recently been shown that talkers are capable of simultaneously adapting multiple vowels to an alteration of auditory feedback during the production of complex, variable sentences [1]. The present study extends this work by examining adaptation to a more complex, physical alteration of the speech motor system (palatal prosthesis) that impacts both auditory and somatosensory feedback. Acoustic and kinematic measures (electromagnetic articulography of the tongue) were used to assess the initial impact of the perturbation on a range of vowels and consonants, as well as learned changes following 20 minutes of practice producing variable sentences with the prosthesis in place. Kinematic analyses revealed robust, systematic perturbation and motor learning effects across all speech sounds, indicating that talkers are capable of rapid adaptation in the production of multiple sounds across the articulatory workspace following a physical alteration of the vocal apparatus.
The chemical composition of μ Leonis

Les observations spectroscopiques de la geante super-riche en metal, μ Leo, sont presentee. Les largeurs equivalentes, les parametres de raies, les parametres atmospheriques (temperature effective, gravite de surface, vitesse de microturbulence), le rapport isotopique 12 C/ 13 C et les abondances en metal sont determines.
Analysis of Antimicrobial Susceptibility in Bacterial Pathogens Associated with Urinary Tract Infections from Beijing Teaching Hospital in China, 2009–2017

Objective Since a urinary tract infection (UTI) is easy to relapse and difficult to treat, the antibiotic resistance rate has increased year by year in recent years. This study was to analyze the characteristics of the common pathogenic bacteria and the changes of antibiotic resistance in urinary system infection, so as to guide the standard use of antibiotics in a clinical urinary tract infection and control nosocomial infection effectively. Methods A total of 5,669 strains of a urinary tract infection in the hospital from January 2009 to December 2017 were retrospectively analyzed. Bacterial identification and the antibiotic sensitivity test (AST) were analyzed by using a VITEK-2 Compact system. Results Of the 5669 pathogens, 3,256 (57.44%) of the strains were Gram-negative bacteria (GNB), 1,474 (26%) were Gram-positive bacteria (GPB), and 939 (16.56%) were fungi. Resistant rates of ESBL-producing strains were all significantly different from non-ESBL-producing strains in Escherichia coli (p < 0.05). The resistance rate of ESBL-producing strains to β-lactam antibiotics was all higher than that of non-ESBL-producing strains in Klebsiella pneumoniae (p < 0.05). The detection rate of vancomycin-resistantEnterococcus faecium and Enterococcus faecalis was 37.3% and 3.1%, respectively, and the detection rate of linezolid-resistantEnterococcus faecium and Enterococcus faecalis was 0.68% and 0%, respectively. The drug resistance rate of candida sp. to fluconazole, itraconazole, and voriconazole was 1.7%, 8.5%, and 3.4%, respectively. No amphotericin B-resistant strains were detected in the research. Conclusions Among the 5669 strains isolated from urinary tract infection patients, GNB were the main pathogens. Escherichia coli was the major pathogen. The resistance rate of ESBLs-producingEscherichia coli was higher than that of non-ESBLs-producingEscherichia coli in general; meanwhile, β-lactam/β-lactamase inhibitors and carbapenems maintained good antimicrobial activity against Escherichia coli. The resistance rate of non-ESBLs-producingKlebsiella pneumoniae strains was significantly higher than that of ESBLs-producingKlebsiella pneumoniae strains, and drug resistance was more prominent; most of the antibiotic resistance rates were over 50%. The antimicrobial resistance rate of Enterococcus faecium was significantly higher than that of Enterococcus faecalis. There were rare linezolid-resistant strains. The antimicrobial resistance rate of imidazole to fungi was controlled less than 10%.
Plasmonic Metasurface-Enabled Differential Photodetectors for Broadband Optical Polarization Characterization

The polarization state of an optical field is central to applications in optical communications, imaging, and data storage as well as furthering our understanding of biological and physical systems. Here we demonstrate two silicon photodetectors integrated with aluminum nanoantennas capable of distinguishing orthogonal states of either linearly or circularly polarized light with no additional filters. The localized plasmon resonances of the antennas lead to selective screening of the underlying silicon from light with a particular polarization state. The planar device, fully compatible with conventional CMOS fabrication methods, incorporates antennas sensitive to orthogonal states of polarization into two back-to-back Schottky photodetectors to produce a differential electrical signal that changes sign as the polarization of an incident optical beam changes from one basis state to the orthogonal state. The non-null response of the devices to each of the basis states expands the potential utility of the ph.
Factors Affecting Working Memory Capacity: a Meta-Analysis Study

Working memory capacity (WMC) is a brain memory system that has a limited ability to process and store temporary information. The purpose of this study was to find out in more detail the factors affecting working memory capacity. The research method uses Meta-analysis quantitatively by combining several research results using Jeffreys's Amazing Statistics Program (JASP) software. The size of the effect used is the odds ratio. Research search using Prisma strategy by searching journal articles from various databases including Scopus, Proquest, Science Direct, CINAHL, and Google Scholar in the last five years from 2019 to 2023. Results Variation between variables is heterogeneous, so this meta-analysis uses a random-effect model, obtained results there is an influence between age on working memory capacity with a combined effect of OR= 3.15 (95% CI 2.10; 4.20), there is an effect of sleep quality on working memory capacity with a combined effect of OR= 6.45 (95% CI 3.51; 9.39), there is an effect of physical activity on working memory capacity with a combined effect of OR=2.84 (1.98; 3.11), there was an effect of listening to music on working memory capacity with a combined effect of OR=3.24 (2.65; 5.13). In conclusion, age, sleep quality, physical activity, and music are factors that affect working memory capacity.
Impact of individual behavior adoption heterogeneity on epidemic transmission in multiplex networks

In recent years, the impact of information diffusion and individual behavior adoption patterns on epidemic transmission in complex networks has received significant attention. In the immunization behavior adoption process, different individuals often make behavioral decisions in different ways, and it is of good practical importance to study the influence of individual heterogeneity on the behavior adoption process. In this paper, we propose a three-layer coupled model to analyze the process of co-evolution of official information diffusion, immunization behavior adoption and epidemic transmission in multiplex networks, focusing on individual heterogeneity in behavior adoption patterns. Specifically, we investigate the impact of the credibility of social media and the risk sensitivity of the population on behavior adoption in further study of the effect of heterogeneity of behavior adoption on epidemic transmission. Then we use the microscopic Markov chain approach to describe the dynamic process and capture the evolution of the epidemic threshold. Finally, we conduct extensive simulations to prove our findings. Our results suggest that enhancing the credibility of social media can raise the epidemic transmission threshold, making it effective at controlling epidemic transmission during the dynamic process. In addition, improving an individuals’ risk sensitivity, and thus their taking effective protective measures, can also reduce the number of infected individuals and delay the epidemic outbreak. Our study explores the role of individual heterogeneity in behavior adoption in real networks, more clearly models the effect of the credibility of social media and risk sensitivity of the population on the epidemic transmission dynamic, and provides a useful reference for managers to formulate epidemic control and prevention policies.
CD4 T cells and toxicity from immune checkpoint blockade

Immune‐related toxicities, otherwise known as immune‐related adverse events (irAEs), occur in a substantial fraction of cancer patients treated with immune checkpoint inhibitors (ICIs). Ranging from asymptomatic to life‐threatening, ICI‐induced irAEs can result in hospital admission, high‐dose corticosteroid treatment, ICI discontinuation, and in some cases, death. A deeper understanding of the factors underpinning severe irAE development will be essential for improved irAE prediction and prevention, toward maximizing the benefits and safety profiles of ICIs. In recent work, we applied mass cytometry, single‐cell RNA sequencing, single‐cell V(D)J sequencing, bulk RNA sequencing, and bulk T‐cell receptor (TCR) sequencing to identify pretreatment determinants of severe irAE development in patients with advanced melanoma. Across 71 patients separated into three cohorts, we found that two baseline features in circulation—elevated activated CD4 effector memory T‐cell abundance and TCR diversity—are associated with severe irAE development, independent of the affected organ system within 3 months of ICI treatment initiation. Here, we provide an extended perspective on this work, synthesize and discuss related literature, and summarize practical considerations for clinical translation. Collectively, these findings lay a foundation for data‐driven and mechanistic insights into irAE development, with the potential to reduce ICI morbidity and mortality in the future.
A Statistical Method for Detecting Gravitational Recoils of Supermassive Black Holes in Active Galactic Nuclei

Abstract We propose an observational test for gravitationally recoiling supermassive black holes in active galactic nuclei, based on a positive correlation between the velocities of black holes relative to their host galaxies, |Δv|, and their obscuring dust column densities, Σdust, both measured along the line of sight. Our findings using a set of toy models implemented to a Monte Carlo simulation imply that models of the galactic centre and of recoil dynamics can be tested by future observations of the potential Σdust–|Δv| correlation. We have also found that the fraction of obscured quasars decreases with |Δv|, for which the predicted trend can be compared to the observed fraction of type II quasars, and can further test combinations of models we may implement.
AN INTRODUCTION TO CHAOTIC DYNAMICAL SYSTEMS

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The Combination Projection Method for Solving Convex Feasibility Problems

In this paper, we propose a new method, which is called the combination projection method (CPM), for solving the convex feasibility problem (CFP) of finding some x * ∈ C : = ∩ i = 1 m { x ∈ H | c i ( x ) ≤ 0 } , where m is a positive integer, H is a real Hilbert space, and { c i } i = 1 m are convex functions defined as H . The key of the CPM is that, for the current iterate x k , the CPM firstly constructs a new level set H k through a convex combination of some of { c i } i = 1 m in an appropriate way, and then updates the new iterate x k + 1 only by using the projection P H k . We also introduce the combination relaxation projection methods (CRPM) to project onto half-spaces to make CPM easily implementable. The simplicity and easy implementation are two advantages of our methods since only one projection is used in each iteration and the projections are also easy to calculate. The weak convergence theorems are proved and the numerical results show the advantages of our methods.
Susceptibility of perivenous macrophages to PRRSV-1 subtype 1 LV and PRRSV-1 subtype 3 Lena using a new vein explant model

Vessel pathology such as increased permeability and blue discoloration is frequently observed with highly pathogenic PRRSV strains. However, data concerning the viral replication in the environment of blood vessels are absent. In the present study, ex vivo models with swine ear and hind leg vein explants were established to study the interaction of PRRSV-1 subtype 1 reference strain LV and highly pathogenic subtype 3 strain Lena with perivenous macrophages. The replication characteristics of these two strains were compared in vein explants by immunofluorescence analysis. The explants maintained a good viability during 48 hours of in vitro culture. We found that CD163-positive macrophages were mainly present around the veins and their number gradually decreased with increasing distance from the veins and longer incubation time. More CD163+Sn- cells than CD163+Sn+ cells (6.6 times more) were observed in the vein explants. The Lena strain demonstrated a higher replication level than the LV strain, with approximately 1.4-fold more infected cells in the surrounding areas of the ear vein and 1.1-fold more infected cells in the leg vein explants at 48 hours post inoculation. In both LV and Lena inoculated vein explants, most infected cells were identified as CD163+Sn+ (> 94%). In this study, an ex vivo vein model was successfully established, and our findings will contribute to a better understanding of the vein pathology during viral infections (e.g., PRRS, classical and African swine fever).