Miracle-dz/UniFAR-FTUs huggingface dataset:
CT colonography for polyp surveillance & MRI features in Crohn’s disease

PART I In this thesis, surveillance CT colonography was evaluated for patients with 6-9 mm polyps as an alternative to colonoscopy in screening for colorectal cancer with CT colonography. We found a high participation rate and a substantial yield for advanced adenomas at surveillance CT colonography. Importantly, no colorectal cancers or adenomas with high-grade dysplasia were detected, suggesting this strategy is safe. By assessing volumetric growth, we demonstrated that one-third of small polyps progressed during a 3-year surveillance period. These growing polyps were more likely to be advanced adenomas than stable or regressing polyps. We also showed that acceptance for surveillance CT colonography was high and burden was low. However, when considering the overall CT colonography screening strategy including the surveillance yield compared to a colonoscopy strategy, there was a significant lower detection rate for serrated adenomas which could potentially influence the value of CT colonography as screening modality. PART II MRI has proven its use in diagnosing and monitoring Crohn’s disease. Numerous MR features have been identified and multiple scorings systems have been developed for assessing and quantifying the degree of inflammation. We determined that the available scoring systems and their incorporated features were comparable in reproducibility, correlation and diagnostic performance. In addition, we determined which MR features were useful in assessing rectal inflammation on perianal MRI. We showed that in addition to wall thickness and mural fat, four features related to the perimural fat tissue were more helpful than the established luminal features.
The Potential and Trend of End-Of-Life Passenger Vehicles Recycling in China

The contradiction between limited resources and rapid development in the automobile industry has been driving society to seek the supply of recyclable resources from End-of-Life Vehicles (ELVs). It has become an urgent need for vehicle recycling policymakers to have an overall understanding of the end-of-life (EoL) vehicle population, as well as for vehicle producers to note what and how they can benefit from ELV recycling. This paper estimated the potential population of EoL passenger vehicles, all recyclable resources from them, as well as the economic values of these recyclable resources. The results show that in 2030, with a lighter-weight trend of passenger vehicles, more than 26.3 million passenger vehicles will be retired with 19.1 million tons of recyclable steel and 6.2 million tons of plastics. The theoretical economic value of all recyclable resources will reach 101.3 billion yuan ($14.4 billion) in 2030, which is an average of approximately 2.4 thousand yuan ($341.8) for each EoL passenger vehicle. It is time for the vehicle producers to shift to a manufacturing mode considering such large potential of ELV recycling. The scenario analysis suggests that in the context of a light-weighting trend, ELV resource recovery in the future calls for improvement in the recycling and reuse technologies of plastics and rubbers.
A study of the physical properties of SB2s with both the visual and spectroscopic orbits

The study of a selected set of 69 double-lined spectroscopic binaries (SB2) with well-defined visual and spectroscopic orbits was carried out. The orbital parallax, the mass, the colour, and the luminosity of each component were derived from observational data for almost all of these systems. We have also obtained an independent estimation of the component masses by comparing the colour–magnitude diagram (CMD) to the stellar evolution tracks reported by Pietrinferni. Nearly all of the observational points on the CMD are located between two tracks of slightly different mass or which fall very close to the one corresponding to a unique mass value. The masses obtained from the stellar model are in good agreement with their empirical values determined by parallax techniques (orbital, Gaia, and dynamical). This means that our adopted model is rather reliable and can therefore be used to infer further information, such as the age of each component in the studied systems. Our results indicate a fair correspondence between the age of primaries and secondary stars within 3σ . Nevertheless, we caution that these age indications suffer of uncertainties due to both inhomogeneities/low precision of the adopted photometric data and possible systematics. Finally, it is statistically shown that along with the orbital and trigonometric parallaxes, the dynamical parallax can serve as a reliable tool for distance estimates.
Sentiment Analysis for Movie Reviews Based on Four Machine Learning Techniques

The spread of Internet and social media led to be sentiment analysis an open research area. Social media is used so the people can be state their opinions and attitudes on blogs, Tweets, and forums. Sentiment analysis deals with identifying and extracting people's opinions and attitudes from texts on the internet. The classification of the text which is based upon sentiment is differ from topical text classification because it has recognition based on an opinion on a topic. This research studying the ability to apply TF-IDF feature selection approach for sentiment analysis and examines the performance for classification by 4 machine learning methods (naïve Bayes, KNN, J48, and logistic regression) with regard to recall, precision and F1-measure. This research included a comparison between the selected ML methods. The results show the naïve Bayes over performed on other classification methods with precision about 94.0% .
COMPREENDENDO O PADRÃO DE PRECIPITAÇÃO USANDO ANÁLISES DE DADOS FUNCIONAIS

Precipitation is one of the most prominent factors in determining the climate of a region. This variable generated by a complex climate system, with high local variability, is the subject of several studies. Given this, this paper aims to study the main sources of variation and to determine the standardized behaviors between different functional curves of the monthly precipitation accumulation series of the municipalities of Recife and Vitória de Santo Antão from January 2000 to December 2018, available from the Pernambuco Water and Climate Agency (APAC), using functional data analysis (FDA). The FDA makes it possible to continuously restructure data without losing information variability. The Fourier base was used to smooth the data because it has a periodic behavior. The principal functional component analysis (FPCA) showed great variation between the months of May, June and July, which are related to the winter months and there was a slight variation for the months of January and February due to the summer storms, where they are associated. to the climatic behavior of the municipalities. Cluster analysis separated the functional groups into groups according to their similarities, which confirmed the groups using the FPCA Biplot. The analysis of functional variance (FANOVA) compared the means of monthly precipitation accumulation, even though the municipalities were relatively close to FANOVA found significant difference (p <0.01) between their averages. Therefore, the analysis of functional data showed a strong flexibility in studying the behaviors of observations showing that with a smaller amount of information, relevant results for the phenomenon can be extracted.
The Effect of Malonic Acid and Succinic Acid on the Corrosion Behavior of Mg-5Zn in (Nh4)3PO4 and NaF

While having excellent biocompatibility and biodegradability properties, magnesium alloys have been widely known to exhibit low corrosion resistance, especially in an acidic environment. The partially protective layer of Mg(OH)2 plays an important role in the corrosion behavior of magnesium, while a phosphate and fluoride conversion film enhances the corrosion resistance of magnesium alloy. The comparative study of electrochemical corrosion behaviour of Mg-5Zn with different media was performed in 1% (NH4)3PO4 and 1% NaF. The effect of malonic and succinic acid on the corrosion behaviour of Mg-5Zn was also analyzed. The back scattering electron mode of scanning electron microscopy was used to characterize the microstructure of Mg-5Zn alloys. Electrochemical impedance spectroscopy (EIS) and the potentiodynamic polarization curve were employed to study the electrochemical corrosion behaviour of Mg-5Zn. It was found that the presence of malonic and succinic acid decreases film resistance and enhances the electron transfer of Mg-5Zn in 1% (NH4)3PO4 and 1% NaF. A higher Mg-5Zn dissolution rate was observed in a binary mixture of 1% malonic acid and 1% succinic acid with 1% (NH4)3PO4 and 1% NaF in comparison with Mg-5Zn in 1% (NH4)3PO4 and 1% NaF.
Forecasting of Wind-Wave Height by Using Adaptive Neuro-Fuzzy Inference System and Decision Tree

Wind-induced waves are considered to be the most important waves in the sea due to their high energy and frequency. Among the characteristics of the waves, height is one of the most important parameters that are used in most equations related to marine engineering designs. Since the application of soft computing methods in marine engineering has been developed in recent years, in present research, an adaptive neuro-fuzzy inference system and a decision tree have been used to predict the wind-induced wave height in Bushehr port. In order to identify the effective parameters, implementing different models from different inputs. By considering the accuracy of the models, the effective parameters in wave height were identified using statistical measures correlation coefficient (r), Mean Square Error (MSE). The final results of this study showed that in the prediction of wind-induced wave height, compared to the decision tree, the accuracy of the model of the neural-fuzzy system for 3, 6 and 9 hours was higher. Also, the results showed that the use of wind shear velocity instead of wind speed at 10 meters above the water level had a higher accuracy in forecasting of the significant wave height. The results also indicated that among the presented models, the combined model of the significant wave height, shear velocity, and the difference between the direction and wind speed as well as the length of the fetch has the highest accuracy.
IDENTIFYING MEDIATORS OF ANDROGEN-INDEPENDENT PROSTATE CANCER USING MASS SPECTROMETRY-BASED PROTEOMICS

Androgen-deprivation remains the principal therapy for advanced and metastatic prostate cancers. However, some cancer cells are able to survive this treatment and transform themselves to a more aggressive androgen-independent prostate cancer (AIPC). An understanding of the molecular alterations that occur during the progression to androgen-independence is of utmost importance in order to generate effective targeted therapies. Using two different in vitro approaches coupled to high through-put mass spectrometry, we were able to identify numerous potential mediators of AIPC and aggressive prostate cancer. Our first approach using an in vitro cell line model of androgen-independence allowed us to identify enzymes of the ketogenic pathway as elevated in cases of aggressive prostate cancer. Specifically, ACAT1, an enzyme in this pathway, was further validated and shown to be substantially elevated in clinical cases of castration-resistant metastatic prostate cancer. In addition, ACAT1 was found to be an independent tissue-based prognostic marker of biochemical recurrence-free survival.
How is a resource for changing teachers’ assessment practice in primary science successfully disseminated, shared and enacted within a primary school?

Many researchers in the field of education aim to inform and improve the pedagogical practice of in-service practitioners through the successful dissemination of their research outputs. Commonly used modes for dissemination include online availability and face-to-face presentation. It is not known which dissemination modes are most effective for a research team, nor what social learning opportunities, characteristics within a teacher workforce, or wider workplace factors might influence how practitioners respond to and engage with such research outputs. This three-part mixed methods study addresses these wider issues through the evaluation of the dissemination of the TAPS pyramid, a resource designed to help primary practitioners to evaluate and improve their assessment practice in primary science. It is situated within sociocultural assumptions of learning as a socially constructed process and draws upon King’s (2003) three levels of dissemination activity as a theoretical framework. Quantitative analyses of download and dissemination event data demonstrate a positive interaction between both online dissemination and dissemination by event; analyses of survey data show variation in engagement with the resource based on job role and experience; expansive workplace characteristics are shown to be significantly linked to reports of whole school use; transactional communication is shown to enable the transfer of new knowledge; and informal learning contacts are valued by participants. The findings are used to elaborate King’s model of dissemination by specifying the activities, inhibitors and enablers of dissemination for action. It is concluded that dissemination of research outputs is facilitated by interactive communication at each stage, entails formal and informal learning opportunities, and its success can be enhanced by the evaluative and leadership skills of the knowledge broker, as well as the wider characteristics of the school as a workplace.
Image classification of malaria using hybrid algorithms: convolutional neural network and method to find appropriate K for K-nearest neighbor

<span>This paper presents image classification algorithms to improve the learning rate and to comparison the classification efficiency. Using convolutional neural network (CNN) for feature extraction and method to find appropriate k for k-nearest neighbor (KNN). Medical datasets were used in the experiments to classify <span>Plasmodium Vivax and Plasmodium Falciparum. Results of the study indicated that for Plasmodium Vivax in ring form, the appropriate k was 1 and the learning rate (LR) was 83.33%, Trophozoite (k=5, LR=91.67%),</span></span><span> Schizont (k=1, LR=83.33<span>%</span>), and Gametocyte (k=1, LR=<span lang="AR-SA" dir="RTL">91.67</span><span>%</span>) whereas </span><span>Plasmodium Falciparum in ring form</span><span> (k=7, LR=91.67%)<span>,</span> Trophozoite (k=1, LR=83.33%), Schizont (k=1, LR=91.67%) and Gametocyte (k=1, LR=100%). </span>
Financial Expectations and Household Consumption: Does Middle Inflation Matter?

Using British panel data, we explore the finding that households often expect their financial position to remain unchanged compared to other alternatives, using a gener- alised middle inflated ordered probit (GMIOP ) model. In doing so we account for the tendency of individuals to choose 'neutral' responses when faced with attitudinal and opinion-based questions, which are a common feature of survey data. Our empirical analysis strongly supports the use of a GMIOP model to account for this response pattern. Expectations indices based on competing discrete choice models are then ex- ploited to explore the role that financial expectations play in driving the consumption of different types of durable goods and the amount of expenditure undertaken. Whilst financial optimism is significantly associated with consumption, indices which fail to take into account middle-inflation are found to overestimate the impact of financial expectations.
Versatile simulations of admixture and accurate local ancestry inference with mixnmatch and ancestryinfer

It is now clear that hybridization between species is much more common than previously recognized. As a result, we now know that the genomes of many modern species, including our own, are a patchwork of regions derived from past hybridization events. Increasingly researchers are interested in disentangling which regions of the genome originated from each parental species using local ancestry inference methods. Due to the diverse effects of admixture, this interest is shared across disparate fields, from human genetics to research in ecology and evolutionary biology. However, local ancestry inference methods are sensitive to a range of biological and technical parameters which can impact accuracy. Here we present paired simulation and ancestry inference pipelines, mixnmatch and ancestryinfer, to help researchers plan and execute local ancestry inference studies. mixnmatch can simulate arbitrarily complex demographic histories in the parental and hybrid populations, selection on hybrids, and technical variables such as coverage and contamination. ancestryinfer takes as input sequencing reads from simulated or real individuals, and implements an efficient local ancestry inference pipeline. We perform a series of simulations with mixnmatch to pinpoint factors that influence accuracy in local ancestry inference and highlight useful features of the two pipelines. Together, mixnmatch and ancestryinfer are powerful tools for predicting the performance of local ancestry inference methods on real data.
Using therapeutic contracts in person-centered counseling and psychotherapy: the perspectives of experienced Greek person-centered therapists

ABSTRACT The therapeutic contract is an important aspect of the counseling process. However, it has received limited research interest, especially in the person-centered community. The objective of this qualitative study was to examine the perceptions and use of therapeutic contracts of seven experienced, person-centered therapists in Greece. A grounded theory design was chosen to guide the analysis of the data that were collected through semi-structured interviews. The emergent theoretical model was conceptualized as a system organized around the core category of ‘Forming a Safe – Attuned Framework’, which included the key-categories ‘Coordination game’, ‘Boundary setting’, and ‘Equal relationship’. Data analysis also revealed the contextual input of the ‘Therapist’s characteristics’ and the contextual output of the ‘Client consequences’. The emergent theory suggests that experienced person-centered therapists utilize therapeutic contracts in the first session with a new client in order to create a safe environment in which they can work cooperatively and develop their relationship. This process is guided by specific characteristics of the therapists (e.g. their sense of professional identity), and leads to various positive consequences for clients (e.g. facilitating their personal freedom). The study has important implications for practicing professionals, as well as for the training of new person-centered therapists.
Satisfaction of Using Mobile Banking in Islamic Banks: TTF and Information Quality Perspective

The purpose of this paper is to evaluate the impact of Fit Technology Task (TTF) and Information Quality (QI) on User Satisfaction (US) mobile banking applications in Islamic banking in Jakarta, Indonesia. Quantitative methodology was used in this study and data was collected through a written questionnaire. The measurement items used in the operationalization of the research instruments were adopted from previous related studies. The findings show that the suitability of technology and tasks of mobile banking customers, and the quality of information about mobile banking applications are important factors that influence customer satisfaction. This research is only limited to the study of the influence of TTF and IQ and still requires further research to observe the factors that influence customer satisfaction in using mobile banking. Through this research, it is expected to be able to make a positive contribution to finance and technology, especially with the development of Fintech (financial technology) and banking technologies such as mobile banking. Practically, this research is expected to contribute to Islamic banking in Indonesia by taking into account the development of mobile banking application technology that is able to provide compatibility between technology and tasks and technology that is able to provide optimal quality information to generate customer satisfaction in using mobile banking.
An Analysis of the Thermal Interaction Between Components in Power Converter Applications

Accurately predicting the temperature of semiconductor devices is very important in the initial design of the power electronics converter. RC thermal models derived from the well-known methods have some ability to predict the temperature. However, the accuracy is boundary condition specific; hence, these methods cannot be used in the reliability analysis. To make the thermal model more accurate and robust, the factors contributing to discrepancies need to be analyzed carefully. These are power-module-materials’ nonlinear properties, thermal grease layer, and the cooling system (i.e., liquid-cooled cold plate). In this article, the estimation of accurate RC parameters from the FEA thermal model is demonstrated in COMSOL. The electrical model having temperature-dependent power loss model is coupled to a refined thermal model and solved in a circuit simulator, PLECS. The proposed method is applied in two applications: assessing thermal interaction between IGBTs and antiparallel diodes in a half-bridge power module and assessing thermal interaction among the discrete switches in an interleaved bidirectional dc–dc converter. Results show that the impact of material nonlinearity, thermal grease layer, and cooling boundary conditions are significant for accurate prediction of IGBT and diode temperatures. The proposed model is consistent with FEA results and differs by 2%–6.5% compared with the experimental results.
Critical Temperatures and Heating Times for Fruit Damage in Northern Highbush Blueberry

Over-canopy sprinkler systems are used to cool northern highbush blueberry (Vaccinium corymbosum L.) fields and maintain fruit quality in the northwestern United States, but more information is needed to determine exactly when cooling is needed. The objective of this study was to identify the critical temperatures for heat damage to berries and for effective evaporative cooling. An initial study conducted in western Oregon in a mature planting of late-season ‘Elliott’ blueberry revealed that heat damage was typically observed within 1 to 3 days after an extreme heat event. Fruit damage, including softening, shriveling, and necrosis, occurred during both green and blue stages of development and was found primarily on sun-exposed berries, which on hot, sunny days (>35 °C) were 7 to 11 °C warmer than the ambient air temperature. A subsequent study was conducted to determine whether the critical temperature for heat damage differed between the green and blue fruit stages. In this case, ‘Aurora’ was compared with ‘Elliott’ blueberry. Berries were heated using a chamber-free convective unit and were exposed for up to 4 hours to berry temperatures of 42, 44, 46, and 48 °C. When the berries were green, significant damage was visible at each temperature within 1.5 to 2 hours in ‘Aurora’ and 3 to 3.5 hours in ‘Elliott’. Damage of green berries increased with time and temperature, and after 4 hours, ranged from 17% to 59% of the total berry number in the cluster in ‘Aurora’ and 10% to 24% in ‘Elliott’. Fruit damage at the blue stage was less than at the green stage and was only significant at 46 and 48 °C (within 3.5 to 2 hours, respectively) in ‘Aurora’ and at 48 °C (within 2 hours) in ‘Elliott’. Wax and cutin layers thickened on the berries as they progressed from green to blue, which perhaps increased their tolerance to heat at later stages of development. Based on these results, northern highbush blueberry fields should be cooled at air temperatures >32 °C during the green stages of fruit development and >35 °C during ripening.