Miracle-dz/UniFAR-FTUs huggingface dataset:
MODELING OF STRUCTURE FORMATION PROCESS IN INTERMETALLIC NiAl ALLOYS DURING THERMOCHEMICAL PRESSING

Mathematical model aimed at obtaining NiAl alloys with a given structure and properties is proposed and implemented, based on the use of data on the features of the physical modeling of the thermochemical pressing process. For a mathematical description of the process of extrusion of a high-temperature synthesis product, it is necessary to determine a system of equations that takes into account the distribution of the thermo-kinetic and rheological properties of the synthesis product in a mold and caliber. High-temperature synthesis of intermetallic compound NiAl in a powder mixture of pure elements in the conditions of thermochemical pressing allows to obtain an intermetallic alloy with an average grain size of ~ 40—50 microns.
GROWTH AND DEVELOPMENT OF BELL PEPPER CROP IRRIGATED WITH MAGNETICALLY-TREATED WATER

This study aimed to evaluate the benefits of irrigation with magnetically-treated water and replacement depths based on ETc, in plant growth and development of bell pepper grown in a protected environment in two cultivation seasons . The experiment was carried out in a protected environment, in the Centro Tecnico de Irrigacao (CTI), at Universidade Estadual de Maringa (UEM), in Maringa - PR. Two experiments were performed: summer (2017-2018) and winter-spring (2018). The experimental design adopted was randomized blocks in factorial scheme 3 x 2 (six treatments) with four replications in the summer season and 2 x 2 (four treatments) with six replications in the winter-spring season. The first factor consisted of water replacement depths (50, 75 and 100% of the evapotranspiration of culture (ETc) in the summer season, and 75 and 100% ETc in the winter-spring season. The second factor was the application of water with and without magnetic treatment. Characteristics of growth (plant height, stem diameter, leaf area, and dry matter of stem, leaf, total, and root) and development (first flower and first fruit) were evaluated. Results showed that there was no significant interaction between the factors for the summer season. There were only isolated effects of replacement depths, and the 100% ETc had the highest values for the growth variables, independent of water treatment. The application of magnetically-treated water provided higher accumulation of dry matter (stem, total, and root) when irrigated with 75% ETc for the winter-spring season.
Effect of Different Veneering Techniques on Shear Bond Strength and Translucency of Bi-layered Zirconia Ceramics

Purpose. This study was designed to compare the effect of different veneering techniques (CAD-on, Press-on and manual layering) on the shear bond strength of veneering ceramics to zirconia framework and translucency of bi-layered zirconia based ceramics. Materials and Methods: A total of forty-eight zirconia samples were fabricated and were divided into three equal groups (n=16) according to the veneering technique used: Group (I): samples veneered using CAD-on technique. Group (II): samples veneered using Press-on technique and Group (III): samples veneered using manual layering technique. The samples of each group were subdivided into two equal subgroups (n=8) according to the testing procedure: Subgroup (A): for translucency parameter (TP). Subgroup (B): for shear bond strength. All samples were thermocycled in thermocycling device. Samples of subgroup (A) were tested for translucency parameter (TP) by using a reflective spectrophotometer. Samples of subgroup (B) were tested by using a universal testing machine. Failure modes of fractured samples were evaluated using stereomicroscope and scanning electron microscope (SEM). Data were statistically analyzed. Results: CAD-on veneered samples, group (1), recorded higher mean translucency parameter (11.099±0.452) than manual layering veneered samples, group (3), which recorded lower translucency parameter (5.463±1.255). CAD-on veneered samples, group (1), recorded higher mean shear bond strength (16.262±4.492) than Press-on veneered samples, group (2) which recorded lower shear bond strength (8.584±1.606). Conclusions: CAD-on veneered samples showed superior translucency parameter and shear bond strength than Press-on veneered samples.
The Effect of Different Cavity Disinfectants on Microleakage and Interfacial Micromorphology of Class V Resin Composite Restorations Using Two Adhesive Systems (SEM-Study)

Purpose: This study was designed to evaluate and compare the effect of different cavity disinfectants on microleakage and interfacial micromorphology of class V resin composite restorations using two adhesive systems. Materials and Methods: Thirty six freshly extracted sound maxillary human premolar teeth were selected. Seventy two standardized class V cavities were prepared on both buccal and lingual surfaces of the selected premolars and randomly divided into three main groups (n=24) according to the cavity disinfectant used (A): silver nanoparticles (A1), ozone (A2), both of them (silver nanoparticles and ozone) (A3). Each group was subdivided into 2 subgroups (n=12) according to the type of the adhesive used (B): total-etch adhesive (B1), self-etch adhesive (B2). All cavities were restored with resin composite according to the manufacturer’s instructions and subjected to thermocycling (500 cycles, 5oC -55oC). Ten cavities from each group were examined for microleakage. The interfacial micromorphology of the remaining 2 cavities was examined by environmental scanning electron microscope (ESEM). Data were expressed in scores. Results: There was a statistical significant difference between the different groups, where the highest leakage scores were found in the silver nanoparticles groups, followed by the combination groups (p ≤ 0.05). While the least leakage scores were found in the ozone groups. Also the highest leakage scores were more frequent in the self-etch groups as well as at the gingival margins of the restorations. Conclusions: Microleakage of class V resin composite restoration is affected by the type of cavity disinfectant; being improved by using ozone though deteriorated by using silver nanoparticles. It is better to use the total etch adhesive rather than the self-etch one.
Indication of recent warming process at the intermediate level in the Tyrrhenian Sea from SOOP XBT measurements

The Tyrrhenian Sea is a sub-basin of the western Mediterranean crossed by intermediate and deep waters from the eastern basin. Across this sub-basin, temperature profiles of the water column from expendable bathythermographs (XBT) have been acquired for sixteen years along transects realized thanks to the use of commercial vessels. Since 1999 an increase of temperature has been observed at intermediate depths even if interspersed with periods of decrease. This increase involves deeper and deeper depths along the years then involving the whole sub-basin in the range 200-800 m in September 2014 when largest anomalies over the whole period are found. The paper shows evidences of this rapid heating, giving insights into the origin and the diffusion of the warmer intermediate waters then showing its evolution in years and its relationship with the Eastern Mediterranean Transient.
Impact of Ramadan Fasting on Biochemical and Exercise Parameters Among Patients Undergoing Exercise-Based Cardiac Rehabilitation

Background Ramadan fasting is an important worship activity for Muslims. It is not known if fasting could have deleterious effect on cardiac patients joining cardiac rehabilitation (CR) program, especially during summer season. Aim To assess the effect of Ramadan fasting on biochemical and exercise parameters among patients undergoing 12-week exercise-based CR program. Patients and methods 53 patients joining CR program in university hospital were included in the study. The patients were divided into two groups according to their Ramadan fasting status. Fasting group included 32 patients, while non-fasting group included 21 patients. All patients underwent supervised exercise-based CR during the month of Ramadan. Plasma osmolality, blood urea and serum creatinine were assessed before CR and during the last week of Ramadan. Lipid profile, echocardiography and exercise parameters were assessed before and after CR program. Results The two groups were similar in baseline characteristics including: risk factors, osmolality, urea, creatinine, lipid profile and hemoglobin values, as well as ejection fraction and exercise parameters. After the program, both groups showed significant improvement in ejection fraction, total cholesterol, LDL and HDL levels. There was also improvement in duration of exercise reached and achieved METs before and after CR program in both groups. An important notice was that fasting did not significantly influence plasma osmolality in either group. Conclusion Ramadan fasting did not change serum osmolality or negatively affect the results of CR among cardiac patients. It appears to be safe to undergo exercise-based CR during Ramadan even in summer season.
3D PHOTOGRAMMETRIC INSPECTION OF RISERS USING RPAS AND DEEP LEARNING IN OIL AND GAS OFFSHORE PLATFORMS

Abstract. The purpose of this paper is to show how deep learning techniques, based on CNNs, can contribute to photogrammetry process to perform geometric inspections of risers on offshore platforms. The photogrammetry process has a problematic related to the relative movements presented in the scene where the images are being acquired (dynamic photogrammetry). As an alternative solution, this work proposes the use of the YOLOv2 architecture, because this detector complies with some requirements of speed and good performance considering the functional requisites of the study executed. Thus, the purpose of this model is to detect risers and i-tubes on offshore platforms, then extract an inspection riser from the scene. Finally, with the images obtained, a 3D reconstruction is performed, followed by the results’ analyses.
Biodegradable chitosan coating for improving quality and controlling Alternaria alternata growth in figs

The objective of this work was to evaluate the effect of a chitosan biodegradable coating (BC), functionalized with cinnamon essential oil and aqueous extract of Roselle calyces, on the quality, respiratory rate, anthocyanin content and antioxidant capacity using the ABTS radical. Figs ‘Black Mission’ of two maturity stages were used. The first maturity stage included purple fruits (14% SST), referred to as “ripe figs”. The second stage was unripe figs, which presented a green color in 25% of its surface (11% SST). Five treatments were applied for each fig maturity stage. 150 g of figs was kept into clamshells packaging at 5 °C for 0, 4, 10, 15 and 21 days, before being transferred to room temperature (20 °C) for 2 more days. The BC structure was evaluated with the use of SEM. Furthermore, quality of this fruits as a result of the use BC and the different storage conditions was determined. The incidence and severity of rotting caused by A. alternata was quantified. The matrix of the BC was porous and heterogeneous. The unripe figs treated with BC and preventive treatments showed a lower weight loss, color change, respiration rate, and anthocyanin content than the control group. Meanwhile, the ripe figs receiving the preventive, curative and coated treatments, only showed the smallest color changes compared to the remaining treatments, but the remaining variables were similar to those of the control group. Finally, A. alternata did not grow at 5 °C in unripe figs but only in the ripe ones. The BC preserved the physicochemical and microbiological quality of unripe figs at 5 °C for 21 days.
University of Groningen Homotypic versus heterotypic continuity of anxiety symptoms in young adolescents

Objective: to investigate homotypic and heterotypic longitudinal patterns of symptoms of separation anxiety disorder (SAD), generalized anxiety disorder (GAD), social phobia (SoPh), panic disorder (PD), and obsessive compulsive disorder (OCD) in young adolescents from the Dutch general population. Method: 2,067 individuals (51.4% girls) from a Dutch community sample, who were assessed for the first time when they were aged 10 to 12 years, were followed up across a period of two years. At both assessments, anxiety symptoms were assessed with the RCADS, a self-report questionnaire. Results: Regression analyses indicated that homotypic continuity was relatively high for SAD, GAD, and SoPh symptoms, and for PD in girls. Conclusions: In many studies, anxiety disorders are treated as one group of disorders, and some widely used assessment instruments, such as the Child Behavior Checklist, do not even contain scales that tap different anxiety dimensions. In the present study, evidence for homotypic continuity was found, especially for symptoms of separation, social, and generalized anxiety, and for symptoms of panic disorder in girls, underscoring the usefulness of making distinctions between different anxiety constructs. R. F. Ferdinand ( ) · G. Dieleman · F. C. Verhulst Department of Child and Adolescent Psychiatry, Erasmus Medical Center, Rotterdam/Sophia Children’s Hospital, Dr. Molewaterplein 60, P.O. Box 2060, 3000 CB Rotterdam, The Netherlands e-mail: r.f. ferdinand@erasmusmc.nl R. F. Ferdinand · J. Ormel Department of Social Psychiatry, University of Groningen, Groningen, The Netherlands
Identifying Error-Prone Transactions in Enterprise Applications

—Independent testing teams use requirements as the basis to develop test cases and automated test scripts. The projects are executed under severe schedule constraints, due to which, the testers have to focus their testing efforts on error-prone and important features. Numerous source code based techniques for identifying error-prone features/components have been developed. However, they are based on source code analysis. Independent testing teams rarely have access to source code and they ﬁnd it difﬁcult to use code based techniques. In many cases, the domain experts use Business Process Model and Notation (BPMN) to represent the business requirements. In this paper, we propose an approach to identify error-prone transactions in enterprise applications using a BPMN. It helps in distinguishing between source code errors and test script errors. We have adapted this approach from an existing source code based technique. Our experiments with the approach show that it can identify the location of actual as well as seeded errors in both source code and test scripts.
Dental Image Analysis Approach Integrates Dental Image Diagnosis

including front and back, just as their encompassing bone; along these lines, periapical pictures are exceptionally useful to imagine expected caries, periodontal bone misfortune, and periapical ailments. All-encompassing radiographic are basic in dentistry since they take into consideration the screening of an expansive anatomical area and simultaneously, requires a generally low radiation portion. 3 The goal . ABSTRACT Introduction: Dentistry is now a big human issue for a day and causes enormous teeth pain. Dental caries is also known as caries and tooth decay, and acids produced by bacteria can cause the loss of teeth. Cavities can be seen from yellow to black in various colours. Symptoms include discomfort without apparent cause, trouble feeding and clear trousers or holes in the teeth. Method: Dental X-ray is useful for dentists, for example, root canal treatment, caries identification and many other abnormalities. The procedure is performed with the awareness of the tooth if it is affected by tooth decay. We will better handle the length of the infected tooth-root canal. Dentists had difficulties in previous years in identifying the teeth and the CNN(Computer Neural Network) technology helps us to accurately distinguish the extreme dental tooth and the root channel length from x-rays. Result: The pictures are pre-processed, segmented and then tooth parameters are removed. Deep learning is widely used as a teacher's tool where a neural network will learn features automatically. For picture analysis, evolutionary networks are widely used. This refers to areas like segmentation, identification of anomalies and diagnosis of diseases. Conclusion: In addition to high heterogeneity, database with several images implemented. Due to this heterogeneity in the database with the number of images, the powerful methodology is required to increase the compatibility and robustness between the studies, neural networks architecture and its results. The proposed Neural network approach detected Dental problems with higher accuracy.
The Effects of Facilitative E-tools on Listening Comprehension and Attitudes Towards English Language

The effectiveness of facilitative e-tools on listening comprehension skills, and how it relates to one’s attitude towards English is the major concern of this study. The results provide a guide to school administrators and curriculum planners to maximize efforts on listening comprehension as a major skill that is not only significant to language learning but also in all disciplines. This quasi-experimental study used standardized pretest and posttest, and a Likert type to measure the listening comprehension level and attitudes in English of 110 Grade 12 students of RC-Al Khwarizmi International College Foundation Incorporated- Senior High School who are enrolled in Multimedia and Information Literacy class, respectively. The results revealed that there is a significant difference on listening comprehension and attitudes towards the English language when exposed to podcasts and vodcasts thus the hypothesis is rejected. The descriptive statistics on the participants’ attitudes towards the English language are almost similar in rating. It is also interpreted that as the listening comprehension level increases, the attitudes towards the English language becomes positive. Hence, if there is an audio-visual facility and training to curriculum implementers, then the students’ skills and attitudes in learning will be enhanced.
THE JOINT SPATIAL AND RADIOMETRIC TRANSFORMER FOR REMOTE SENSING IMAGE RETRIEVAL

Abstract. Content-based remote sensing image retrieval refers to searching interested images from a remote sensing image dataset that are similar to a query image via extracting features (contents) from images and comparing their similarity. In this work, we come up with a lightweight network structure, which we call the joint spatial and radiometric transformer, which is composed of three modules: parameter generation network (PGN), spatial conversion and radiometric conversion. The PGN module learns specific transformation parameters from input images to guide subsequent spatial and radiometric conversion processes. With these parameters, the spatial conversion and radiometric conversion transform the input images with spatial and spectrum perspectives respectively, to increase the intra-class similarity and inter-class difference, which are attached great importance to CBRSIR. In comparative experiments on multiple remote sensing image retrieval datasets, our proposed joint spatial and radiometric transformer combined with the backbone network ResNet34 has achieved optimal performance.
Spam Detection Approach for Secure Mobile Message Communication Using Machine Learning Algorithms

The spam detection is a big issue in mobile message communication due to which mobile message communication is insecure. In order to tackle this problem, an accurate and precise method is needed to detect the spam in mobile message communication. We proposed the applications of the machine learning-based spam detection method for accurate detection. In this technique, machine learning classifiers such as Logistic regression (LR), K-nearest neighbor (K-NN), and decision tree (DT) are used for classification of ham and spam messages in mobile device communication. The SMS spam collection data set is used for testing the method. The dataset is split into two categories for training and testing the research. The results of the experiments demonstrated that the classification performance of LR is high as compared with K-NN and DT, and the LR achieved a high accuracy of 99%. Additionally, the proposed method performance is good as compared with the existing state-of-the-art methods.
STYLE SYNTHESIZING CONDITIONAL GENERATIVE ADVERSARIAL NETWORKS

STYLE SYNTHESIZING CONDITIONAL GENERATIVE ADVERSARIAL NETWORKS Yarkın Deniz Çetin M.S. in Computer Engineering Advisor: Selim Aksoy Co-Advisor: Ramazan Gökberk Cinbiş January 2020 Neural style transfer (NST) models aim to transfer a particular visual style to a image while preserving its content using neural networks. Style transfer models that can apply arbitrary styles without requiring style-specific models or architectures are called universal style transfer (UST) models. Typically a UST model takes a content image and a style image as inputs and outputs the corresponding stylized image. It is, therefore, required to have a style image with the required characteristics to facilitate the transfer. However, in practical applications, where the user wants to apply variations of a style class or a mixture of multiple style classes, such style images may be difficult to find or simply non-existent. In this work we propose a conditional style transfer network which can model multiple style classes. While our model requires training examples (style images) for each class at training time, it does not require any style images at test time. The model implicitly learns the manifold of each style and is able to generate diverse stylization outputs corresponding to a single style class or a mixture of the available style classes. This requires the model to be able to learn one-to-many mappings, from an input single class label to multiple styles. For this reason, we build our model based on generative adversarial networks (GAN), which have been shown to generate realistic data in highly complex and multi-modal distributions in numerous domains. More specifically, we design a conditional GAN model that takes a semantic conditioning vector specifying the desired style class(es) and a noise vector as input and outputs the statistics required for applying style transfer. In order to achieve style transfer, we adapt a preexisting encoder-decoder based iii
Early Visual Cortex Stimulation Modifies Well-Consolidated Perceptual Gains.

Perception thresholds can improve through repeated practice with visual tasks. Can an already acquired and well-consolidated perceptual skill be noninvasively neuromodulated, unfolding the neural mechanisms involved? Here, leveraging the susceptibility of reactivated memories ranging from synaptic to systems levels across learning and memory domains and animal models, we used noninvasive brain stimulation to neuromodulate well-consolidated reactivated visual perceptual learning and reveal the underlying neural mechanisms. Subjects first encoded and consolidated the visual skill memory by performing daily practice sessions with the task. On a separate day, the consolidated visual memory was briefly reactivated, followed by low-frequency, inhibitory 1 Hz repetitive transcranial magnetic stimulation over early visual cortex, which was individually localized using functional magnetic resonance imaging. Poststimulation perceptual thresholds were measured on the final session. The results show modulation of perceptual thresholds following early visual cortex stimulation, relative to control stimulation. Consistently, resting state functional connectivity between trained and untrained parts of early visual cortex prior to training predicted the magnitude of perceptual threshold modulation. Together, these results indicate that even previously consolidated human perceptual memories are susceptible to neuromodulation, involving early visual cortical processing. Moreover, the opportunity to noninvasively neuromodulate reactivated perceptual learning may have important clinical implications.