Miracle-dz/UniFAR-FTUs huggingface dataset:
Study of mandibular growth in patients treated with Fränkel´s functional regulator (1b)

Objectives: The purpose of this study was to assess mandibular growth in patients with Class II division 1 malocclusions when treated with Fränkel´s functional regulator 1b. Study Design: The treatment group was made up of 43 patients that were divided into two groups: prepubescent (n:28), and pubescent (n:15). The control group included 40 patients who did not receive any kind of treatment and were likewise divided into a prepubescent group (n:19), and a pubescent group (n:21). A computerized cephalometric study was carried out and superimpositions were done in order to assess the antero-posterior, vertical and rotational movements of the mandible. A two-way ANOVA with interaction was done to compare the changes between the control group and the treatment group, while the Student t for independent samples was used to compare each age group. Results: The Gnathion and Gonion points showed significant differences in the whole sample (p<0.001) as well as in the prepubescent (p<0.001) and pubescent groups (p<0.05). Rotational changes of the mandible measured using the facial axis and mandibular plane showed no statistical differences between both groups (p>0.05). Conclusion: The results show that the FR produces vertical orthopedic growth in the mandible but not horizontal growth compared to non-treated Class II-type I malocclusion patients. No rotational changes were found in the mandible, but we did record mandibular growth along the inclination of the facial axis. Key words:Fränkel appliance, orthodontics, functional appliances, mandibular growth.
Pharmacological versus microvascular decompression approaches for the treatment of trigeminal neuralgia: clinical outcomes and direct costs

In idiopathic trigeminal neuralgia (TN) the neuroimaging evaluation is usually normal, but in some cases a vascular compression of trigeminal nerve root is present. Although the latter condition may be referred to surgery, drug therapy is usually the first approach to control pain. This study compared the clinical outcome and direct costs of (1) a traditional treatment (carbamazepine [CBZ] in monotherapy [CBZ protocol]), (2) the association of gabapentin (GBP) and analgesic block of trigger-points with ropivacaine (ROP) (GBP+ROP protocol), and (3) a common TN surgery, microvascular decompression of the trigeminal nerve (MVD protocol). Sixty-two TN patients were randomly treated during 4 weeks (CBZ [n = 23] and GBP+ROP [n = 17] protocols) from cases of idiopathic TN, or selected for MVD surgery (n = 22) due to intractable pain. Direct medical cost estimates were determined by the price of drugs in 2008 and the hospital costs. Pain was evaluated using the Numerical Rating Scale (NRS) and number of pain crises; the Hospital Anxiety and Depression Scale, Sickness Impact Profile, and satisfaction with treatment and hospital team were evaluated. Assessments were performed at day 0 and 6 months after the beginning of treatment. All protocols showed a clinical improvement of pain control at month 6. The GBP+ROP protocol was the least expensive treatment, whereas surgery was the most expensive. With time, however, GBP+ROP tended to be the most and MVD the least expensive. No sequelae resulted in any patient after drug therapies, while after MDV surgery several patients showed important side effects. Data reinforce that, (1) TN patients should be carefully evaluated before choosing therapy for pain control, (2) different pharmacological approaches are available to initiate pain control at low costs, and (3) criteria for surgical interventions should be clearly defined due to important side effects, with the initial higher costs being strongly reduced with time.
Outcome of Kidney Transplantation Using Expanded Criteria Donors and Donation After Cardiac Death Kidneys: Realities and Costs

Expanded criteria donors (ECDs) and donation after cardiac death (DCD) provide more kidneys in the donor pool. However, the financial impact and the long‐term benefits of these kidneys have been questioned. From 1998 to 2005, we performed 271 deceased donor kidney transplants into adult recipients. There were 163 (60.1%) SCDs, 44 (16.2%) ECDs, 53 (19.6%) DCDs and 11 (4.1%) ECD/DCDs. The mean follow‐up was 50 months. ECD and DCD kidneys had a significantly higher incidence of delayed graft function, longer time to reach serum creatinine below 3 (mg/dL), longer length of stay and more readmissions compared to SCDs. The hospital charge was also higher for ECD, ECD/DCD and DCD kidneys compared to SCDs, primarily due to the longer length of stay and increased requirement for dialysis ($70 030, $72 438, $72 789 and $47 462, respectively, p < 0.001). Early graft survival rates were comparable among all groups. However, after a mean follow‐up of 50 months, graft survival was significantly less in the ECD group compared to other groups. Although our observations support the utilization of ECD and DCD kidneys, these transplants are associated with increased costs and resource utilization. Revised reimbursement guidelines will be required for centers that utilize these organs.
Machine Learning Insights into Student Success

The global youth cohort represents a beacon of hope for the future of the world's population. The implementation of diverse solutions tailored to the unique needs of students poses a significant challenge for Higher Education Institutions (HEIs) situated in underdeveloped countries. The significance of academic achievement in educational institutions is held in high regard by educators, as it serves as a metric to gauge the effectiveness of a particular school. The timely detection of educators who are at risk and the subsequent implementation of proactive measures have been shown to have a substantial impact on their likelihood of achieving success. The educational trajectory of an individual is influenced by a variety of factors, including but not limited to the environment in which they grow up, their family history, and their social and personal responsibilities. These factors collectively contribute to the shaping of an individual's educational journey. The present study employs the Random Forest, Naive Bayes, and K* methodologies to assess the academic performance of students across various dimensions. The experimental research demonstrates that the random forest method exhibits superior performance when compared to both the K* and Naive Bayes approaches.
Enhancing Cybersecurity: A Deep Dive into Augmented Intelligence Through Machine Learning and Image Processing

In cybersecurity, the potential of Machine Learning (ML) is widely acknowledged, yet the evolving landscape of cyber threats necessitates more dynamic and responsive strategies. This paper explores the integration of augmented intelligence with machine learning and image processing to elevate threat detection capabilities and foster effective human-machine collaboration in cybersecurity. We aim to investigate the synergistic potential of combining augmented intelligence with machine learning and image processing. Our approach involves a fusion of human expertise and Artificial Intelligence (AI) capabilities for providing AI-driven insights under human oversight. Additionally, we delve into the role of image processing as a core component of augmented intelligence in broadening the cybersecurity domain. The integration of image processing facilitates the analysis of network traffic through visualizations, the detection of image-based threats, and improved situational awareness. Coupled with machine learning, this methodology empowers cybersecurity systems to effectively detect anomalies, interpret complex network structures, and rapidly identify potential threats. The paper presents empirical evidence supporting the efficacy of this integrated approach.
Formal Property Verification for Early Discovery of Functional Flaws in Digital Designs: A Designer's Guide

Rising digital design complexity and demands for a shorter time to market increasingly challenge functional correctness. Formal verification can prevent flaws due to ambiguities and hard-to-find corner case issues. However, it is primarily attributed to verification engineers and formal experts. We consider that (a) Formal Property Verification (FPV) for sanity checking can contribute to finding flaws early, and (b) more guidance can promote a higher adoption rate by designers. Thus, we propose a concise, tool-agnostic, and flow-chart-based methodology to demystify FPV from a designer's perspective. We showcase the flow in two case studies using designs with different formal suitability, walk through the parts & phases to make the steps more tangible, and point out the limitations.
Learning Individualized Automatic Content Magnification in Gaze-based Interaction

The precision of modern commercial off-the-shelf eye trackers has reached a level sufficient for developing gaze-based applications. In many but not all applications, accuracy even allows for replacing a computer mouse with gaze-bazed pointing. The Multi-Modal Interaction Concept for Efficient input (M2ice) tackles accuracy problems with an on-demand hybrid fisheye magnifier. This paper introduces an image-analysis-based approach that identifies areas on the screen where to automatically activate magnification for improved interaction. It combines the separate actions magnifying and clicking into one seamless action. The approach works by combining OpenCV filters for detection of clickable elements on the screen with a local machine learning algorithm predicting whether magnification is needed based on size and position of screen elements. A user study (n = 28) showed a significant speed increase of 18.50 percent (t(27)=-3.95, p=. 0002 at α = . 05) with automatic magnification compared to separate shortcuts for clicking and magnification.
Short-Term Directional Variability of the Continuum Range in the Deep-Ocean Internal Wave Field

A simple method (Zalkan, 1970) to examine the directionality of the internal wave field has been applied to temperature data at 1000 m depth from the IWEX trimooring (Briscoe, 1975). Results suggest the concept of a horizontally-isotropic deep-ocean internal wave field is not valid over 75-hour periods, but only over a longer time average. The estimated wavenumbers, for each frequency examined, lie along the calculated dispersion relation for modes 1-4.
Circulation current reduction for a motor simulator system using a power converter with a common mode transformer

This paper presents a new suppression method of circulation current for a motor simulator system. A conventional system requires a large transformer at grid frequency to avoid a circulation current between the motor simulator and a test inverter, besides a regenerative converter is required too. In the proposed topology, the high frequency components of the circulation current are suppressed by a common mode transformer, and the low frequency components are suppressed by zero phase current control. Furthermore, a small size medium frequency common mode transformer is used instead of the regenerative converter and the grid frequency transformer. In addition, the proposed system can simulate the transient condition of the motor. The proposed method is validated based on the simulation and experimental results. The motor simulator primary current waveform agrees well with that of the actual motor, including the distortion due to a voltage error by a dead time period. Also the low frequency component of the circulation current was suppressed to less than 1% of the fundamental component by using the proposed method.
Discussion as a Factor in Racial Disparity in Advance Directive Completion at Nursing Home Admission

Studies have consistently shown racial disparities in advance directive completion for nursing home residents but have not examined whether this disparity is due to differences in interactions with healthcare providers. This study had two aims: to determine whether the racial disparity in advance directive completion by nursing home residents is related to differences in discussion of treatment restrictions with healthcare providers and to examine whether there is a racial disparity in perceptions of residents' significant others that additional discussions would be helpful. Participants were 2,171 white or black (16% of sample) residents newly admitted to 59 nursing homes. Data were collected from structured interviews with residents' significant others and review of nursing home charts. Questions included whether advance directives were completed, whether treatment restrictions were discussed with the resident or family, and whether more discussion would have been helpful. Frequencies according to race were determined for each question; P‐values and logistic regression models were obtained. Black residents were less likely to have completed any advance directives (P<.001), and they (P<.001) and their family members (P<.001) were less likely than whites to have discussed treatment restrictions with healthcare providers. Logistic regression models indicated that disparity in treatment restrictions narrowed when these discussions occurred. Significant others of black residents were more likely than those of white residents to consider further discussion helpful (P<.001), especially with physicians. Racial disparity in treatment restrictions may be due in part to a difference in discussion with healthcare providers; increasing discussion may narrow this disparity.
SURVEY OF NEARBY FGK STARS AT 160 μm WITH SPITZER

The Spitzer Space Telescope has advanced debris disk science tremendously with a wealth of information on debris disks around nearby A, F, G, K, and M stars at 24 and 70 μm with the MIPS photometer and at 8–34 μm with IRS. Here we present 160 μm observations of a small subset of these stars. At this wavelength, the stellar photospheric emission is negligible and any detected emission corresponds to cold dust in extended Kuiper Belt analogs. However, the Spitzer 160 μm observations are limited in sensitivity by the large beam size which results in significant “noise” due to cirrus and extragalactic confusion. In addition, the 160 μm measurements suffer from the added complication of a light leak next to the star's position whose flux is proportional to the near-infrared flux of the star. We are able to remove the contamination from the leak and report 160 μm measurements or upper limits for 24 stars. Three stars (HD 10647, HD 207129, and HD 115617) have excesses at 160 μm that we use to constrain the properties of the debris disks around them. A more detailed model of the spectral energy distribution of HD 10647 reveals that the 70 and 160 μm emission could be due to small water ice particles at a distance of 100 AU, consistent with Hubble Space Telescope optical imaging of circumstellar material in the system.
Graph Representation Learning with Graph Transformers in Neural Combinatorial Optimization

Neural combinatorial optimization aims to use neural networks to speed up the solving process of combinatorial optimization problems, i.e., finding the optimal solution of a problem instance from a finite set of feasible solutions that minimize a given objective function. Recently, researchers have applied convolutional neural networks to predict the optimal solution's cost (defined by the objective function) to give as extra input to an exact solver to speed up the solving process. In this paper, we investigate whether graph representations that explicitly model the inherent constraints in combinatorial optimization problems would improve the performance of predicting the optimal solution's cost. Specifically, we use graph neural networks with neighborhood aggregation and graph Transformer models to capture and embed the knowledge in the graph representations of combinatorial optimization problems. We also propose a benchmark dataset containing the Traveling Salesman Problem (TSP) and Job-Shop Scheduling Problem (JSSP), and through the empirical evaluation, we show that graph Transformer models achieve an average loss decrease of 61.05% on TSP and 66.53% on JSSP compared to the baseline convolutional neural networks.
Measurement variability in Heidelberg Retina Tomograph imaging of neuroretinal rim area.

PURPOSE To investigate the optimal frequency of imaging during follow-up to detect glaucoma progression by characterizing variability (noise) in neuroretinal rim area (RA) measured by Heidelberg Retina Tomograph (HRT; Heidelberg Engineering, Heidelberg, Germany). METHODS RA noise was estimated from patient data and characterized by fitting theoretical distributions to the observed data. Multilevel regression was used to determine factors that significantly affect noise. Computer simulations of disease progression were performed by adding noise generated from the distribution derived from the observed data to the average rate of loss in RA estimated from longitudinal data. Rates of detection of disease progression were investigated for various progression rates, follow-up periods, and rates of imaging. RESULTS Noise was not normally distributed and was best characterized by the hyperbolic distribution, which fit averages well while allowing for extreme values. Noise was greatly influenced by image quality, but age did not have a significant effect. Rates of detection improved for more frequent imaging, better quality images, and faster rates of disease progression. CONCLUSIONS Noise in HRT measurement of RA is well characterized by the hyperbolic distribution. Sensitivity of detection improves with more frequent testing, but if consistently poor-quality images are yielded for a patient, the probability of detection is low. Results from this work could be used to tailor individual follow-up patterns for patients with different rates of RA loss and image quality, especially in a clinical trial setting.
User Engagement in Financial Education on Metaverse

The study intents to assess the efficacy of metaverse in influencing users’ engagement in financial education. TAM is used as hypothetical framework in the study comprising perceived ease of use (PEOU) and perceived usefulness (PU) as the exogeneous variables and the intention to use is engaged as antecedent affecting the user engagement. A predetermined questionnaire was used to gather the responses and the same was evaluated applying SEM method. The study findings demonstrate that PEOU and PU are significant indicator of users’ intention in determining the user engagement in the financial literacy on metaverse provided it is easy and hassle-free. The study extends valuable insights to the online financial educational stakeholders to assess, design and device immersive extended reality models for effective learning.
Magnetic Resonance Imaging for Rapid Screening for the Nephrotoxic and Hepatotoxic Effects of Microcystins

In vivo visualization of kidney and liver damage by Magnetic Resonance Imaging (MRI) may offer an advantage when there is a need for a simple, non-invasive and rapid method for screening of the effects of potential nephrotoxic and hepatotoxic substances in chronic experiments. Here, we used MRI for monitoring chronic intoxication with microcystins (MCs) in rat. Male adult Wistar rats were treated every other day for eight months, either with MC-LR (10 μg/kg i.p.) or MC-YR (10 μg/kg i.p.). Control groups were treated with vehicle solutions. T1-weighted MR-images were acquired before and at the end of the eight months experimental period. Kidney injury induced by the MCs presented with the increased intensity of T1-weighted MR-signal of the kidneys and liver as compared to these organs from the control animals treated for eight months, either with the vehicle solution or with saline. The intensification of the T1-weighted MR-signal correlated with the increased volume density of heavily injured tubuli (R2 = 0.77), with heavily damaged glomeruli (R2 = 0.84) and with volume density of connective tissue (R2 = 0.72). The changes in the MR signal intensity probably reflect the presence of an abundant proteinaceous material within the dilated nephrons and proliferation of the connective tissue. T1-weighted MRI-is a valuable method for the in vivo screening of kidney and liver damage in rat models of intoxication with hepatotoxic and nephrotoxic agents, such as microcystins.
Extra-articular Snapping Hip

Context: Snapping hip, or coxa saltans, is a vague term used to describe palpable or auditory snapping with hip movements. As increasing attention is paid to intra-articular hip pathologies such as acetabular labral tears, it is important to be able to identify and understand the extra-articular causes of snapping hip. Evidence Acquisition The search terms snapping hip and coxa sultans were used in PubMed to locate suitable studies of any publication date (ending date, November 2008). Results: Extra-articular snapping may be caused laterally by the iliotibial band or anteriorly by the iliopsoas tendon. Snapping of the iliopsoas tendon usually requires contraction of the hip flexors and may be difficult to differentiate from intra-articular causes of snapping. Dynamic ultrasound can help detect abrupt tendon translation during movement, noninvasively supporting the diagnosis of extra-articular snapping hip. The majority of cases of snapping hip resolve with conservative treatment, which includes avoidance of aggravating activities, stretching, and anti-inflammatory medication. In recalcitrant cases, surgery to lengthen the iliotibial band or the iliopsoas tendon has produced symptom relief but may result in prolonged weakness. Conclusions: In treating active patients with snapping soft tissues around the hip, clinicians should recognize that the majority of cases resolve without surgical intervention, while being mindful of the potential for concomitant intra-articular and internal snapping hips.
Complex Event Processing in Heterogeneous Domains

The technique of recording and evaluating (processing) streams of data about occurrences and drawing conclusions from them is known as Complex Event Processing, or CEP. In recent years, due to ever-increasing security concerns, CEP is being applied increasingly broadly in heterogeneous domains in order to detect potentially dangerous events early or even prevent their occurrence; possible examples are bank robberies in the context of video surveillance, or identity theft in the domain of social network analysis. For such reasons, in this paper we propose a survey reporting the most interesting and innovative approaches to complex event processing in heterogeneous domains; specifically, here we focus on video analysis, social network analysis, and healthcare, classifying the papers into different subcategories and highlighting their advantages and disadvantages.