Miracle-dz/UniFAR-FTUs huggingface dataset:
Summating potential and action potential ratio in Meniere's disease before and after treatment.

OBJECTIVE This study aimed to compare the summating potential and action potential ratio (SP:AP) in patients with Meniere's disease before and after various surgical and medical treatments as an indication of change in endolymphatic hydrops to study the progression of Meniere's disease. STUDY DESIGN The study design was a retrospective case review. SETTING The study was conducted at an otology-neurotology referral center. PATIENTS Eighty-eight ears of 84 patients with Meniere's disease received medical treatment in 18 ears and surgical treatments including endolymphatic shunt in 12 ears, streptomycin perfusion of the lateral semicircular canal in 9 ears, streptomycin perfusion of the middle ear in 33 ears, and dexamethasone perfusion of the middle ear in 16 ears. INTERVENTION Transtympanic electrocochleography (ECoG) was performed in all patients before treatment and 1-57 months after treatment (mean, 13.5 months) with a 2-year interval in 28 patients. MAIN OUTCOME MEASURE An enlarged SP:AP ratio (> or = 0.40) was used as the diagnostic criterion for endolymphatic hydrops. RESULTS Overall, an enlarged SP:AP ratio was found in 75% of ears before treatment and 78% after treatment. The SP:AP ratio, when enlarged, remained enlarged in 91% of ears. A nonenlarged SP:AP ratio before treatment became enlarged after treatment in 41% of ears. In American Academy of Otolaryngology-Head and Neck Surgery stage 1 Meniere's disease (pure-tone threshold average < or = 25 dB), an enlarged SP:AP was found in 58% of ears before treatment and 79% after. Twenty-five (89%) of 28 patients followed for 2 years were free of vestibular symptoms after treatment, and in 22 patients (79%), the SP:AP remained enlarged. The distribution of an enlarged SP:AP ratio was associated with the duration of disease (chi-square = 33.5552, p < 0.01). CONCLUSIONS The development of endolymphatic hydrops, as indicated by an enlarged SP:AP, is part of the progression of Meniere's disease. The longer the duration of the disease, the more likely the SP:AP ratio will be enlarged. These findings indicate that endolymphatic hydrops as detected by ECoG was not reversed in this study by the treatments used. Despite the absence of definitive spells of vertigo in most patients, endolymphatic hydrops as evidenced by an enlarged SP:AP ratio persisted.
Comparison of Anthropogenic Aerosol Climate Effects among Three Climate Models with Reduced Complexity

The same prescribed anthropogenic aerosol forcing was implemented into three climate models. The atmosphere components of these participating climate models were the GAMIL, ECHAM, and CAM models. Ensemble simulations were carried out to obtain a reliable estimate of anthropogenic aerosol effective radiative forcing (ERF). The ensemble mean ERFs from these three participating models with this aerosol forcing were −0.27, −0.63, and −0.54 W∙m−2. The model diversity in ERF is clearly reduced as compared with those based on the models’ own default approaches (−1.98, −0.21, and −2.22 W∙m−2). This is consistent with the design of this aerosol forcing. The modeled ERF can be decomposed into two basic components, i.e., the instantaneous radiative forcing (RF) from aerosol–radiation interactions (RFari) and the aerosol-induced changes in cloud forcing (△Fcloud*). For the three participating models, the model diversity in RFari (−0.21, −0.33, and −0.29 W∙m−2) could be constrained by reducing the differences in natural aerosol radiative forcings. However, it was difficult to figure out the reason for the model diversity in △Fcloud* (−0.05, −0.28, and −0.24 W∙m−2), which was the dominant source of the model diversity in ERF. The variability of modeled ERF was also studied. Ensemble simulations showed that the modeled RFs were very stable. The rapid adjustments (ERF − RF) had an important role to play in the quantification of the perturbation of ERF. Fortunately, the contribution from the rapid adjustments to the mean ERF was very small. This study also showed that we should pay attention to the difference between the aerosol climate effects we want and the aerosol climate effects we calculate.
Estimating the Maximum Likelihood Root Mean Square Error of Approximation (RMSEA) with Non-normal Data: A Monte-Carlo Study

Recent research has provided formulae for estimating the maximum likelihood (ML) RMSEA when mean or mean and variance, corrections for non-normality are applied to the likelihood ratio test statistic. We investigate by simulation which choice of corrections provides most accurate point RMSEA estimates, confidence intervals, and p-values for a test of close fit under normality, and in the presence of non-normality. We found that, overall, any robust corrections (choices MLM, MLMV, and MLR) provide better results than ML, which assumes normality. When they err, all choices tend to suggest that the model fits more poorly than it really does. Choice MLMV (mean and variance corrections) provided the most accurate RMSEA estimates and p-values for tests of close fit results but its performance decreases as the number of variables being modeled increases.
Recognizing Global Reservoirs From Landsat 8 Images: A Deep Learning Approach

Man-made reservoirs are key components of terrestrial hydrological systems. Identifying the location and number of reservoirs is the premise for studying the impact of human activities on water resources and environmental changes. While complete bottom-up censuses can provide a comprehensive view of the reservoir landscape, they are time-consuming and laborious and are thus infeasible on a global scale. Moreover, it is challenging to distinguish man-made reservoirs from natural lakes in remote sensing images. This study proposes a convolutional neural network (CNN)-based framework to recognize global reservoirs from Landsat 8 imageries. On the basis of the HydroLAKES dataset, a Landsat 8 cloud-free mosaic of 2017 was clipped for each feature (reservoir or lake) and was resized into 224 × 224 patches, which were collected as training and testing samples. Compared to other deep learning methods (Alexnet and VGG) and state-of-the-art traditional machine learning methods (support vector machine, random forest, gradient boosting, and bag-of-visual-words), we found that fine-tuning the pretrained CNN model, ResNet-50, could reach the highest accuracy (91.45%). Application cases in Kansas (USA, North America), Mpumalanga (South Africa, Africa), and Kostanay (Kazakhstan, Asia) resulted in classification accuracies of better than 99%, which showed the applicability of the proposed ResNet-50 model to the extraction of reservoirs from a vast amount of moderate resolution images. The framework that was developed in this paper is the first attempt to combine remote sensing big data and the deep learning technique to the recognition of reservoirs at a global scale.
Thromboelastography parameters versus classical coagulation profile in trauma patients: Retrospective study

Background: Thrombelastography (TEG) assesses the viscoelastic properties of the whole blood and it is more comprehensive and capable to detect any coagulation abnormalities in comparison to classical coagulation tests (CCTs). On this ground, TEG can be more efficient in acute settings. Therefore, the primary aim was to compare TEG parameters of traumatic brain injury (TBI) versus non-TBI (NTBI) patients. The secondary aim was to identify TEG versus CCT parameters associated with outcome. Methods: A cross-sectional retrospective observational study of 142 patients admitted to a university-based, Level 1 trauma center. TEG and CCT were collected on admission. Institutional Review Board approval was obtained for this study. SAS was used for categorical data were analyzed using Chi-square or Fisher's exact test. A comparison of continuous variables between TBI and NTBI patients was performed using the independent-sample t-test. Results: In a total of 142 patients, 48 patients had TBI and 94 patients did not. Overall, mortality was 20.4% (45.8% TBI vs. 7.4% NTBI). There were no significant associations between TEG or CCT parameters and studied variables some of which are injury severity score, abbreviated injury scale, craniotomy/ectomy, type of brain injury, discharge status, and blood pressure. There was no difference between the TBI and NTBI groups regarding TEG or CCT parameters. Maximum amplitude (MA) was the only parameter (TEG or CCT) associated with need for transfusion of packed red blood cell (PRBC) (P = 0.0377). PRBC transfusion was given in 94% of patients with an MA <57.4. Platelet transfusion was given in 89% of patients who have MA < 58.1. Fresh-frozen plasma (FFP) transfusion was given in 80% of patients who have R ≥5.8. PRBC transfusion was given in 77% of 18 patients with α <62.9. Conclusions: TEG parameters are potentially useful as means to rapidly diagnose coagulopathy and predict transfusion in trauma patients. Independently, the presence of TBI does not cause a detectable coagulopathy. TEG analysis is more efficient than the classical parameters in detecting patients who will need PRBC and FFP transfusion.
Investigating the Relationship Between Satellite-Based Freeze/Thaw Products and Land Surface Temperature

This paper investigates surface temperature variables as they relate to passive microwave-derived surface freeze/thaw (FT) state and assesses the accuracy of such FT products relative to surface temperature. Utilizing retrievals from the soil moisture active/passive (SMAP), advanced microwave scanning radiometer, and special sensor microwave imager instruments, surface FT records have previously been derived globally. Moderate Resolution Imaging Spectroradiometer skin temperature, North American Land Data Assimilation System (NLDAS) skin, 0–10-cm soil layer, and 2-m air temperatures are compared to the various FT state products (FTSPs) by defining the threshold for FT state transitions at 0 °C. This paper utilizes the 2015–2016 overlap period in FT records within the NLDAS domain. Spatial variability of classification accuracy (CA) is then investigated over the study area. A proportional differencing method also enables the identification of biases between FTSPs and surface temperature variables. Additionally, by analyzing probability distribution functions of FTSPs associated with temperature values, we assess the distribution of temperature variables as they relate to FT classifications. Classification agreement is shown to vary with sensor configuration, seasonality, and retrieval time. Air temperature is found to have the highest CAs across FTSPs (81%–91%), while NLDAS soil exhibits a close relationship to FTSPs, especially in regard to SMAP products. Finally, ascending (p.m.) retrievals are shown to be increasingly linked to the selected temperature parameters as compared to descending (a.m.) observations. This paper contributes to an improved understanding of current FTSPs and will benefit efforts to enhance future FT products.
Master thesis : Multi-band IR sensor for Earth Observation

A new CubeSat is in development by students and professors of the University of Liège and the Centre Spatial de Liège. The CubeSat OUFTI-NEXT will measure the hydric stress in crop fields in order to enhance the management efficiency of the water resources for agriculture. This CubeSat incorporates a thermal imager to capture the electromagnetic radiation of the infrared band. In this project, it is analysed the performance of the different infrared detectors that can be used within the CubeSat optical instrument. There are a few examples of CubeSat missions observing in the Mid-Wave Infrared Band or in the Long-Wave Infrared band. However, any of these missions can observe in both bands at the same time. This Master Thesis describes the feasibility of an optical instrument for a CubeSat observing in both bands with the use of a single detector. With this aim, the performance of the two main groups of infrared detectors, photodetectors and thermal detectors, is measured in terms of temperature resolution and signal-to-noise ratio in the space environment. These computations are carried on with the model of equations developed in this Master Thesis.
MALA-within-Gibbs Samplers for High-Dimensional Distributions with Sparse Conditional Structure

Markov chain Monte Carlo (MCMC) samplers are numerical methods for drawing samples from a given target probability distribution. We discuss one particular MCMC sampler, the MALA-within-Gibbs sampler, from the theoretical and practical perspectives. We first show that the acceptance ratio and step size of this sampler are independent of the overall problem dimension when (i) the target distribution has sparse conditional structure, and (ii) this structure is reflected in the partial updating strategy of MALA-within-Gibbs. If, in addition, the target density is block-wise log-concave, then the sampler's convergence rate is independent of dimension. From a practical perspective, we expect that MALA-within-Gibbs is useful for solving high-dimensional Bayesian inference problems where the posterior exhibits sparse conditional structure at least approximately. In this context, a partitioning of the state that correctly reflects the sparse conditional structure must be found, and we illustrate this process in two numerical examples. We also discuss trade-offs between the block size used for partial updating and computational requirements that may increase with the number of blocks.
USO DA TÉCNICA DE MINERAÇÃO DE DADOS PARA ESTUDO DA INFLUÊNCIA DE FATORES METEOROLÓGICOS SOBRE A PRODUÇÃO DE TOMATE PARA PROCESSAMENTO INDUSTRIAL

O Tomate industrial e uma das hortalicas de maior importância economica no estado de Goias e no Mundo. O objetivo deste trabalho e comprovar, pelo metodo de mineracao de dados, quais as variaveis que influenciam na classificacao do ciclo do cultivo, produtividade, qualidade e teor de solidos soluveis (oBrix) do tomate industrial. Foram analisadas as medias por ciclo do cultivo das seguintes variaveis: temperatura, precipitacao pluviometrica e umidade relativa do ar. Outra variavel analisada foi a Altitude do cultivo. Com a classificacao atraves da mineracao de dados foi possivel concluir que o as variaveis temperatura, precipitacao e umidade durante o ciclo do cultivo impactam na produtividade do tomate industrial no municipio de Morrinhos estado de Goias conforme os outros estudos ja consolidados nesta area.
Cooperative Task Offloading in Three-Tier Mobile Computing Networks: An ADMM Framework

The deployment of cloud and edge computing forms a three-tier mobile computing network, where each task can be processed locally, by the edge nodes, or by the remote cloud server. In this paper, we consider a cooperative three-tier computing network by leveraging the vertical cooperation among devices, edge nodes and cloud servers, as well as the horizontal cooperation between edge nodes. In this network, we jointly optimize the offloading decision and the computation resource allocation to minimize the average task duration subject to the limited battery capacity of devices. However, the formulated problem is a large-scale mixed integer non-linear optimization problem with the growing number of base stations and devices, which is NP-hard in general. To develop an efficient offloading scheme with low complexity, we conduct a series of reformulation based on reformulation linearization technology and further propose a parallel optimization framework by utilizing alternating direction method of multipliers (ADMM) method and difference of convex functions (D.C.) programming. The proposed scheme decomposes the large-scale problem into some smaller subproblems, which are done across the multiple computation units in a parallel fashion to speed up the computation process. Simulation results demonstrate that the proposed scheme can obtain a near-optimal performance with low complexity, and can reduce up to 24% of the task duration compared with other schemes. Simulation also shows how much the vertical and horizontal computation cooperations affect the system performance under different network parameters.
Early onset frontotermporal dementia and alzheimers disease: diagnosis, treatment and care

This research investigated two groups of patients diagnosed with dementia before the age of sixty-five. The patients were diagnosed with Alzheimer's Disease (AD, n = 25) and Frontotemporal Dementia (FTD, n = 37). Patients were assessed for approximately 3 years. The study found that FTD is a valid and useful diagnostic category, and can be reliably differentiated from AD. A combination of behavioural, neurological, and neuropsychological assessments were found to be complementary in the early and accurate diagnosis of early-onset dementia, and the differential diagnosis of FTD from AD. FTD patients were found to have relatively preserved visuo-spatial abilities compared to the AD patients. Problems associated with administering neuropsychological tests to early-onset dementia patients were highlighted. FTD patients were found to deteriorate more rapidly than AD patients, and to have significantly increased behavioural disturbances throughout the course of the illness in comparison with the AD patients. Practical guidelines to assist with care and management of early-onset dementia patients were presented. A strengths-based model of care was outlined. Individualised assessments and care plans were recommended for the development and provision of humane services to early-onset dementia patients. Issues surrounding providing palliative care were discussed.
Experimental determination of the electro-acoustic properties of thin film AlScN using surface acoustic wave resonators

In this work, all electroacoustic material parameters, i.e., the elastic, piezoelectric, and dielectric coefficients, as well as the mass density, were determined experimentally for wurtzite aluminum scandium nitride (Al 1 − xSc xN) for a wide range of Sc concentrations of up to x = 0.32 from the same material source for the first time. Additionally, the mass density and piezoelectric coefficient were determined even up to x = 0.42. Two sets of 1 μm-thick AlScN(0001) thin films were deposited on Si(001) using reactive pulsed-DC magnetron cosputtering. One set of thin films was used to determine the a- and c- lattice parameters and the effective relative dielectric coefficient e 33 , f, using X-ray diffraction and capacitive measurements, respectively. Lattice parameters were then used to extract average internal parameter u, bond length, and bond angle, as well as mass density, as a function of Sc concentration. Density functional theory calculations were performed to provide the equilibrium lattice parameters a, c, and u, as well as the bond angle and the bond lengths for wurtzite-AlN and layered hexagonal-ScN. The second set of films was used to fabricate surface acoustic wave (SAW) resonators with wavelengths λ from 2 up to 24 μm. The SAW dispersion in conjunction with finite element modeling fitting was used to extract the elastic stiffness as well as the piezoelectric coefficients. The overall evolution of the material parameters and the change of the crystal structure as a function of Sc concentration is discussed in order to provide a possible explanation of the observed behavior.In this work, all electroacoustic material parameters, i.e., the elastic, piezoelectric, and dielectric coefficients, as well as the mass density, were determined experimentally for wurtzite aluminum scandium nitride (Al 1 − xSc xN) for a wide range of Sc concentrations of up to x = 0.32 from the same material source for the first time. Additionally, the mass density and piezoelectric coefficient were determined even up to x = 0.42. Two sets of 1 μm-thick AlScN(0001) thin films were deposited on Si(001) using reactive pulsed-DC magnetron cosputtering. One set of thin films was used to determine the a- and c- lattice parameters and the effective relative dielectric coefficient e 33 , f, using X-ray diffraction and capacitive measurements, respectively. Lattice parameters were then used to extract average internal parameter u, bond length, and bond angle, as well as mass density, as a function of Sc concentration. Density functional theory calculations were performed to provide the .
Reading comprehension, Mathematics self-efficacy perception, and Mathematics attitude as correlates of students’ non-routine Mathematics problem-solving skills in Turkey

Literature that investigates the factors affecting problem-solving evaluates the cognitive and affective components, such as reading comprehension, metacognition, Mathematics anxiety, Mathematics attitude and Mathematics self-efficacy. Recently, studies have shown that Mathematics attitude and Mathematics self-efficacy as affective factors, and reading comprehension as a cognitive factor could play a crucial role in the problem-solving of middle school students. This study investigated the influence of reading comprehension skill, Mathematics self-efficacy perception and Mathematics attitude on non-routine Mathematics problem-solving skills. It is hypothesized that non-routine problem-solving skills are related to reading comprehension skills, Mathematics self-efficacy perception and Mathematics attitudes. To achieve this aim, a reading comprehension skill test, a Mathematics self-efficacy perception scale, a Mathematics attitude scale and a non-routine problem-solving skill test were applied. The instruments were completed by 362 middle school students. A correlation analysis was used to determine the relationship of variables on non-routine problem-solving skills, and the predictive effects of the predictor variables on non-routine Mathematics problem-solving skills were examined by hierarchical regression analysis. The analysis also showed that for middle-school students’ non-routine Mathematics problem-solving skills, all related factors–reading comprehension, Mathematics self-efficacy perception and Mathematics attitude were significant. Reading comprehension skills and Mathematics self-efficacy perception significantly predicted problem-solving skills, and both predictors explained a total of 22% of the total variance.
Defining a role for the cystic fibrosis transmembrane conductance regulator in the heart

59 Introduction. 60 Materials and methods. 61 Results and Discussion . 62 References. 66 Figures . 68 Chapter 4: In vitro and in vivo examination of CFTR in β-adrenergic stimulated heart function 74 Abstract. 74 Introduction. 75 Materials and methods. 77 Results . 80 Discussion. 85 References. 88 Figures . 93 Appendix: Additional characterization of cardiomyocyte contraction rate and the ion channels/transporters involved in its regulation . 110 Effect of non-selective CFTR inhibitors on cardiomyocyte contraction rate. 110 Role of hyperpolarization-activated ‘funny’ channels in cardiomyocyte contraction rate . 111 Role of HCO3 and external ATP in cardiomyocyte contraction rate . 111 Effect of swelling-activated Cl channel inhibition on cardiomyocyte contraction rate . 113 Effect of 4,4,-diisothiocyanostilbene sulfonic acid (DIDS) on cardiomyocyte contraction rate . 113