Miracle-dz/UniFAR-FTUs huggingface dataset:
Albertina in Action: An Investigation of its Abilities in Aspect Extraction, Hate Speech Detection, Irony Detection, and Question-Answering

O campo de processamento de linguagem natural testemunhou avanços significativos nas últimas décadas, impulsionados pela aplicação de aprendizado profundo. Combinando com o uso de uma arquitetura neural chamada Transformers, os avanços são ainda mais superiores e marcantes. Neste trabalho, usamos um modelo baseado em BERT para a língua portuguesa do Brasil, chamado Albertina, nas tarefas de Extração de Aspecto, Detecção de Discurso de Ódio, Detecção de Ironia e Perguntas-Respostas. Por fim, comparamos os resultados obtidos em cada tarefa com os modelos de base e grande de BERTimbau e Albertina.
Malignant lung PEComa (clear cell tumor): rare case report and literature review

Clear cell tumors of the lung (CCTL), or “sugar tumors” of lung, are very uncommon lesions and are mostly benign perivascular epithelioid cell (PEC) tumors with no specific morphologic features. Fewer than 100 cases have been reported; the aggressive nature demonstrated in sporadic reports has rarely been described in the literature. Although the course is generally described as benign, eight reported cases showed malignant behavior. We report a case of a PEC with a malignant presentation in a young man, correlating the main characteristics of the tumor with other cases reported in the literature to better elucidate this rare presentation. We also performed a literature review of reports on benign and malignant CCTL cases, with a focus on clinical, imaging, and immunohistochemical differentiation. CCTLs are rare tumors that require histopathological and immunohistochemical confirmation; to date, criteria that can predict malignant evolution are lacking.
Calibrating Shenandoah watershed SWAT model using a nonlinear groundwater algorithm

Title of Thesis: CALIBRATING SHENANDOAH WATERSHED SWAT MODEL USING A NONLINEAR GROUNDWATER ALGORITHM Yan Wang, Master of Science, 2011 Directed By: Dr. Kaye Brubaker Water Resources Engineering Department of Civil and Environmental Engineering This study contributes to a project with the Interstate Commission on the Potomac River Basin to build a model of the Potomac watershed using the Soil Water Assessment Tool (SWAT). The 2,937 mi Shenandoah watershed represents about 40% of the Potomac Basin by area. The model subdivides the Shenandoah watershed into 28 subwatersheds and 489 hydrologic response units. SWAT‘s linear-reservoir groundwater algorithm is modified into a new nonlinear method. Modeled flows are compared to observations (dating from 1996 to 2006) at 15 USGS stream gages. The model is auto-calibrated using the Parameter Estimation Software (PEST), experimenting with options to improve model performance. The best model results are obtained by applying ordinal weights to the observation groups, decreasing from headwaters to outlet, and pre-calibrating the roughness coefficients using empirical equations. The calibrated model will contribute to understanding hydrological processes and predicting the effects of land use and climate change in the watershed. CALIBRATING SHENANDOAH WATERSHED SWAT MODEL USING A NONLINEAR GROUNDWATER ALGORITHM
THE EFFECT OF BAI, SIZE, OWNERSHIP, AND PROFITABILITY ON DISCLOSURE OF BIOLOGICAL ASSET

Data from the Ministry of Agriculture showed that during the Covid-19 pandemic, agricultural sector managed to increase the growth of GDP by 2.19% compared to the previous year (year-on-year). Then, data from the Central Bureau of Statistics shows in 2020, only the agricultural sector made a positive contribution of 1.75% to GDP compared to other business sectors. This needs to be the government's attention to develop the agricultural sector as a sector that is expected to be the main engine of development in order to realize the Sustainable Development Goals (SDGs). The intention of this research was to find out the effect from intensity of biological asset, firm size, managerial ownership and profitability on disclosure of biological assets in agricultural enterprises listed on the IDX from 2016 to 2020. This study falls under verification research category. All agricultural companies listed on IDX period 2016-2020 are the population in this research. Purposive sampling was used to choose the sample and 13 companies were chosen. Documentary studies were used to acquired data. In this study, data was collected utilizing a documentary study with analysis of multiple linear regression. In this study data processing using the help of IBM SPSS Ver.25. 0. According to the findings of this study, firm size has a considerable favorable effect on the dsiclosure of biological assets. The intensity of biological assets, management ownership, and profitability no impact disclosure of biological assets. Thus, biologiccall aset intensity, firm size, managerial oownerhip, and profitability silmutaneously impact on biological aset disclosure.
Comparison of the Three Methods of Psychotherapy on Marital Satisfaction and Intimacy in Married Women

Marital satisfaction and intimacy are influential factors in psychological well-being. Psychotherapy can be effective in promoting them. This study aimed to compare the effect of three methods of Emotion-Focused Couple Therapy, Acceptance and Commitment Therapy, and Imago Relationship Therapy on Marital Satisfaction and Intimacy in married women. This is a semi-experimental study in which three groups of women took part. Thirty-nine married women completed the study (Emotion-Focused Couple Therapy: 14, Acceptance and Commitment Therapy (ACT): 14, and Imago Relationship Therapy: 11). Data were collected using ENRICH Marital Satisfaction Scale and Intimacy Scale. Data were analyzed using SPSS v. 22 via one-way ANOVA and t-tests. The findings indicated the effectiveness of Emotion-Focused Couple Therapy (3.37±1.27 vs. 4.79±0.68), Acceptance and Commitment Therapy (3.35±0.35 vs. 4.19±0.16), and Imago Relationship Therapy (3.52±0.15 vs. 4.17±0.16) on intimacy (p=0.001, Partial Eta Squared=0.30); and effectiveness of Emotion-Focused Couple Therapy (203.70±14.88 vs. 273.33±8.26), Acceptance and Commitment Therapy (202.11±16.29 vs. 208.71±13.66), and Imago Relationship Therapy (200.08±7.51 vs. 438.01±17.82) on marital satisfaction (p=0.001, Partial Eta Squared=0.98). Emotion-Focused Couple Therapy, Acceptance and Commitment Therapy, and Imago Relationship Therapy had a large effect size on the intimacy and marital satisfaction of married women. Imago Relationship Therapy was clinically the most effective therapy.
Leveraging natural cognitive systems in conjunction with ResNet50-BiGRU model and attention mechanism for enhanced medical image analysis and sports injury prediction

Introduction In this study, we explore the potential benefits of integrating natural cognitive systems (medical professionals' expertise) and artificial cognitive systems (deep learning models) in the realms of medical image analysis and sports injury prediction. We focus on analyzing medical images of athletes to gain valuable insights into their health status. Methods To synergize the strengths of both natural and artificial cognitive systems, we employ the ResNet50-BiGRU model and introduce an attention mechanism. Our goal is to enhance the performance of medical image feature extraction and motion injury prediction. This integrated approach aims to achieve precise identification of anomalies in medical images, particularly related to muscle or bone damage. Results We evaluate the effectiveness of our method on four medical image datasets, specifically pertaining to skeletal and muscle injuries. We use performance indicators such as Peak Signal-to-Noise Ratio and Structural Similarity Index, confirming the robustness of our approach in sports injury analysis. Discussion Our research contributes significantly by providing an effective deep learning-driven method that harnesses both natural and artificial cognitive systems. By combining human expertise with advanced machine learning techniques, we offer a comprehensive understanding of athletes' health status. This approach holds potential implications for enhancing sports injury prevention, improving diagnostic accuracy, and tailoring personalized treatment plans for athletes, ultimately promoting better overall health and performance outcomes. Despite advancements in medical image analysis and sports injury prediction, existing systems often struggle to identify subtle anomalies and provide precise injury risk assessments, underscoring the necessity of a more integrated and comprehensive approach.
Distinguishing Liquid Solutions With Alcohol Using Electrical Impedance Measurements: Preliminary Study for Food Safety Applications

Methods for identifying contaminants in liquids (such as wine) typically require laboratory analyses of samples using precision equipment, which is expensive in terms of both time and required resources. Therefore, there is a need to identify alternative measurement approaches to reduce the cost in terms of equipment, personnel, and time. One sensing approach to characterize liquid properties and potentially identify contaminants is electrical impedance spectroscopy (EIS). In this work, the electrical impedance of 25-mL samples of three solutions with alcohol (plum distillate, isopropyl alcohol, and winter windshield solution) and a control sample of distilled water were measured using a Keysight 4294A. The liquids with alcohol content (plum distillate, isopropyl alcohol, and winter windshield solution) have lower impedance magnitude in the frequency band below 100 kHz, with specific values of 139, 76, and 7 <inline-formula> <tex-math notation="LaTeX">$\text{k}\Omega $ </tex-math></inline-formula> at 40 Hz, compared to the reference distilled water sample (approximately 315 <inline-formula> <tex-math notation="LaTeX">$\text{k}\Omega $ </tex-math></inline-formula>). This suggests that solutions with alcohol (and other chemicals) have increased conductivity in comparison to the distilled water and that impedance may be a suitable approach to differentiate liquids with and without contaminants.
Deep Generative Modeling Based on VAE-GAN for 3D Indoor Scene Synthesis

With the advancement of virtual reality and 3D game technology, the demand for high-quality 3D indoor scene generation has surged. Addressing this need, this paper presents a method leveraging a VAE-GAN-based framework to conquer two primary challenges in 3D scene representation and deep generative networks. First, we introduce a matrix representation to encode fine-grained object attributes, alongside a complete graph to implicitly capture object spatial relations—effectively encapsulating both local and global scene structures. Second, we devise a unique generative framework based on VAE-GAN and the Bayesian optimization. This framework learns a Gaussian distribution of encoded object attributes through a VAE-GAN network, allowing for sampling and decoding of the distribution to generate new object attributes. Subsequently, a U-Net is employed to learn spatial relations between objects. Lastly, the Bayesian optimization module amalgamates the generated object attributes, spatial relations, and priors learned from data, conducting global optimization to generate a logical scene layout. Experimental results on a large-scale 3D indoor scene dataset substantiate that our method effectively learns inter-object relations and generates diverse and plausible indoor scenes. Comparative experiments and user studies further validate that our method surpasses the current state-of-the-art techniques in indoor scene generation and is comparable to real training scenes.
Realistic Expectations for Rock Identification.

Successful hand-specimen rock identification for beginning students is dependent upon providing representative samples with clearly observable properties and insuring student understanding of both rock-forming processes and the construction of the classification scheme being used. Minerals classification can be clear cut and definitive because minerals are compounds that have definite internal structures and definite chemical compositions (or compositions that vary within limits as, for example, in the plagioclase feldspars). In contrast, rock-classification schemes have boundaries that are necessarily arbitrary because rocks are mixtures of minerals that are formed by gradational processes. Classification of specimens that happen to fall near boundaries is often subjective; one person's basalt may be another person's gabbro. This seemingly obvious point is not trivial and when overlooked can lead to frustration and anxiety for students who believe they must make definitive decisions about samples which t.
The selection of intra-inter specific Cucurbita rootstocks for grafted melon seedlings

This study was conducted to select promising Turkish local Cucurbita rootstocks among intraspecific and interspecific hybrids for grafted melon seedling based on hybrid success rate, hypocotyl traits and graft compatibility. Rooting potentials, root system architecture and plant growth parameters of the rootstocks grafted with melon were also evaluated. Two lines of C. maxima (male parent) and eleven lines of C. moschata (female parent) at S5 generation were used. In addition, six winter squash lines were used as male parent and six pumpkin lines were used as female parent in intraspecific hybridization program. Intraspecific hybrid combinations had quite high number of seeds per fruit as compared to interspecific hybrid combinations. The highest number of seeds per fruit was obtained from HMO2 × OMO2 (359) and OMO5 × HMO8 (314) hybrid combinations. Hypocotyl lengths of all hybrid cucurbit rootstock combinations ranged from 32.96 mm (RS17) to 73.35 mm (RS8) and hypocotyl thicknesses ranged from 2.71 mm (RS2) to 3.55 mm (RS8). Graft success rates varied between 96.6 – 100% in winter squash and pumpkin intraspecific hybrids and between 87.1 – 100% in interspecific hybrids. Significant differences were seen in root architecture parameters (root length, root volume, mean root diameter, root surface area and root dry matter weight) of intraspecific and interspecies hybrid Cucurbita lines. The findings of the study indicated that the intraspecific and interspecific local cucurbit rootstock candidates developed within the rootstock breeding program showed promise as viable options for commercial use as rootstocks for grafted melon seedlings. Research about the effects of selected intraspecific and interspecific hybrid Cucurbita rootstock candidates on earliness, fruit quality and yield parameters of grafted melon will continue. Keywords: Cucurbita maxima; Cucurbita moschata; Rootstock breeding; Root system architecture; Melon
Dosimetric Comparision of Coplanar versus Noncoplanar Volumetric Modulated Arc Therapy for Treatment of Bilateral Breast Cancers

Introduction: The purpose of this study was to compare the dosimetric parameters of volumetric modulated arc therapy (VMAT) treatment plans using coplanar and noncoplanar beams in patients with bilateral breast cancer/s (BBCs) in terms of organ at risk sparing and target volume coverage. The hypothesis was to test whether VMAT with noncoplanar beams can result in lesser dose delivery to critical organs such as heart and lung, which will result in lesser overall toxicity. Materials and Methods: Data of nine BBC cases treated at our hospital were retrieved. Computed tomography simulation data of these cases was used to generate noncoplanar VMAT plans and the parameters were compared with standard VMAT coplanar plans. Contouring was done using radiation therapy oncology group guidelines. Forty-five Gray in 25 fractions was planned followed by 10 Gy in five fractions boost in breast conservation cases. Results: No significant difference in planning target volume (PTV) coverage was found for the right breast/chestwall (P = 0.940), left breast/chestwall (P = 0.872), and in the total PTV (P = 0.929). Noncoplanar beams resulted in better cardiac sparing in terms of Dmean heart. The difference in mean dose was >1 Gy (8.80 ± 0.28 − 7.28 ± 0.33, P < 0.001). The Dmean, V20 and V30 values for total lung slightly favor noncoplanar beams, although there was no statistically significant difference. The average monitor units (MUs) were similar for coplanar plans (1515 MU) and noncoplanar plans (1455 MU), but the overall treatment time was higher in noncoplanar plans due to more complex setup and beam arrangement. For noncoplanar VMAT plans, the mean conformity index was slightly better although the homogeneity indices were similar. Conclusion: VMAT plans with noncoplanar beam arrangements had significant dosimetric advantages in terms of sparing of critical organs, that is Dmean of heart doses with almost equivalent lung doses and equally good target coverage. Larger studies with clinical implications need to be considered to validate this data.
Optimal power flow solution using opposition based modified Rao’s algorithm

Optimal Power flow (OPF) is crucial in a power system, and this is essential for continuous monitoring of the system’s current status, system stability, extension of the system, best operation of the system, etc. This paper applies Particle Swarm Optimization (PSO) and proposed Opposition-based Modified Rao’s (OMR) algorithms for OPF solutions with various technical constraints. In this paper, the objectives are to minimize the total generation cost, total real power loss, sum of squared voltage stability index, and total voltage deviation and to know performance parameters in terms of real and reactive power flows, voltage profile, load bus voltage deviations, load angle and voltage stability indices. To see the effectiveness of the proposed OMR algorithm, IEEE standard 30-bus system is considered and tested. The results obtained with the proposed OMR algorithm are better than the other techniques in the literature.
Effect of Fear on the Interrelationships of the Domains of Destination Image

COVID-19 pandemic, which triggered fear, has affected the tourism industry globally, and Philippine tourism was not an exception. Gen Z travelers, an underexplored generation, are seen to play a key factor in tourism innovations. Further, destination image in the context of COVID-19 pandemic has not yet been widely explored. This study aims to investigate the effect of Filipino Gen Z’s COVID-19 fear on their perception of cognitive, affective, and conative image. Partial least squares structural equation modelling (PLS-SEM) revealed that Gen Z’s COVID-19 fear did not have a significant effect on destination image. Significant positive relationships among the destination image components were proven. Affective image mediated the relationship between cognitive and conative images. The study contributes to the limited studies on Gen Z’s and their destination image perception during the pandemic. It encourages organizations and marketers to focus on Gen Z travelers to form positive destination image during the pandemic.
Assessment of the nutritional status of school children in Galle Municipality area: A comparison between different body mass index classification systems

Introduction: Asian populations are at an increased risk of cardiometabolic disorders due to higher fat mass at a relatively lower body mass index (BMI). Several discrepancies have been reported in the BMI classification systems currently in practice to assess the nutritional status among children. Aim of this study was to compare the different international BMI based classification systems to identify the nutritional status in a cohort of Sri Lankan children.Methods: A cross sectional study was conducted on 833 (48.37% boys) school children aged 5-15 years in Galle Municipality area, Sri Lanka. The nutritional status of each child was defined according to five BMI classification systems: World Health Organization (WHO), Centers for Disease Control and Prevention(CDC), and International Obesity Task Force (IOTF), Indian and Sri Lankan systems. The agreement between them was tested using Cohen’s kappa coefficient.Results: Prevalence of under-weight, overweight and obesity of children, as determined by the WHO, CDC, IOTF, Indian and the Sri Lankan classification systems showed significant differences. The WHO classification system had the best agreement (k=0.649) with the Indian classification system. A wide difference between the Sri Lankan classification system (24.37%) and the Indian (9.60%) and WHO (5.04%) classification systems in defining obesity were observed.Conclusion & recommendations: A wide difference between different BMI classification systems when determining the nutritional status in children emphasise the importance of developing a country-specific classification system to identify the nutritional status among Sri Lankan children.
Geochemical analysis of SAR backscattering (Sentinel-1) on global ocean oil spill cases

ABSTRACT The oil spill is one of the most impactful sources of marine pollution on the ocean surface, detected by the SAR sensors as dark areas, regions with low backscatter values. Due to the complex mixture of hydrophobic hydrocarbons, mineral oil spills change the water surface tension dampening the capillary gravity waves and provoking a specular reflection. In this work, we associated the geochemical oil characteristics, such as density, viscosity, API, and molecular composition with the backscatter values for each oil spill case. We identified the relationship between the oil weathering processes, with the changes in the backscattering values of ocean oil spills. The method designed zonal sections over the oil spills detected in the SAR images, to extract the backscatter values for each pixel along the section. The lowest backscatter average was observed by the heavy oil spill in the Corsica Island study (−29,99 dB). The highest level of weathering had the highest backscatter averages. Damping rates ranged between 4,12 and 7,07 dB and the backscatter values may be related to low oil layer thickness. Furthermore, low wind speeds may have reduced the contrast between water and oil spills, resulting in low damping ratios in all events.
Butterflies (Lepidoptera: Papilionoidea) of the urban park of Instituto Butantan, São Paulo, Southeastern Brazil

Green areas in urban landscapes are under strong anthropogenic pressure, and, at the same time are fundamental to maintaining biodiversity, as they provide resources for many animal and plant species. Knowing these species is fundamental for its maintenance and conservation, and inventories are extremely important for monitoring fauna and conserving it. Therefore, the goal of this research is to inventory the butterflies species in the park of the Instituto Butantan (Ibu), located in an urban area in the city of São Paulo, southeast Brazil. The surveys of butterflies were conducted through visual censuses from August 2017 to July 2019 and recorded a total of 324 butterfly species. The most speciose family was Hesperiidae, followed by Nymphalidae, Lycaenidae, Pieridae, Riodinidae, and Papilionidae. Among the sampled species, there is Euselasia zara which is a new record for the state of São Paulo. Neither the species accumulation nor the richness estimator curves tended to reach an asymptote, suggesting that additional butterflies’ species will be recorded with more sampling effort on the site. Even with a flora composed mainly of exotic and ornamental plants, the park of Instituto Butantan exhibits a very rich butterfly community. This community exhibits a pattern of seasonally variation, with the peak of species richness related to the rainy season. When compared with Cidade Universitária Armando de Salles Oliveira (USP), another nearby urban green area, which is larger, more heterogeneous and sampled over a longer period, it is possible to notice that the Ibu butterfly community is a subsample of this larger one. These results highlight the potential that urban parks have for the maintenance and conservation of butterfly species.