Miracle-dz/UniFAR-FTUs huggingface dataset:
Event-based summarization of news articles

: In recent years, with the increase of available digital information on the Web, the time needed to find relevant information is also increased. Therefore, to reduce the time spent on searching, research on automatic text summarization has gained importance. The proposed summarization process is based on event extraction methods and is called an event-based extractive single-document summarization. In this method, the important features of event extraction and summarization methods are analyzed and combined together to extract the summaries from single-source news documents. Among the tested features, six features are found to be the most effective in constructing good summaries. The constructed summaries are tested on benchmark Document Understanding Conferences 2001 and 2002 datasets, and the results outperformed most of the other well-known summarization methods.
A Nonintrusive Magnetically Coupled Sensor for Measuring Liquid Level

A new, linear, nonintrusive, and cost-effective inductive liquid level sensor is designed and developed. The sensor consists of a simple coil that floats on the liquid surface. A couple of printed planar coils partially surround the liquid column and sense the position of the floating coil and hence the liquid level. The planar coils are arranged with overlap such that the floating coil is always in proximity to both the coils. The coils are excited, and their response is processed, such that the final output is proportional to the liquid level. The input–output characteristics of the proposed liquid level measurement are linear, with a worst case percentage nonlinearity < 1%. A prototype sensor built for a range of 180 mm, had a resolution of 0.73 mm. The output of the prototype has very low sensitivity to the position of the floating coil in the xy plane, indicating that the movement of the floating coil on the surface of the liquid column does not affect the liquid level measurement. Since the sensing part is just made of passive elements, the lifetime of the sensor can be made very high.
Just-in-time performance without warm-up

Scala has been developed as a language that deeply integrates with the Java ecosystem. It offers seamless interoperability with existing Java libraries. Since the Scala compiler targets Java bytecode, Scala programs have access to high-performance runtimes including the HotSpot virtual machine. HotSpot provides impressive performance results achieved via just-in-time compilation. It starts program execution in interpreter mode, collecting profile feedback about called methods. This information allows HotSpot to identify hot spots in the program, which are then compiled on the fly to native code. This compilation scheme enables high peak performance at the cost of warmup time required to collect the profile data and perform just-in-time compilation. This is a good example of the traditional tradeoff between ahead-of-time (AOT) and just-intime (JIT) compilation. With AOT, compilers have less information, but the runtime story is reasonably straightforward. With JIT, compilers have more information, which enables advanced optimizations, but the runtime story becomes complicated. In this dissertation, we present the design and implementation of Scala Native, an optimizing compiler for Scala. With Scala Native, Scala programs are compiled ahead of time, which avoids runtime compilation and enables instant startup times. On the other hand, Scala Native is able to match and supersede the peak performance of HotSpot on our benchmarks. In addition to that, Scala Native is a general-purpose Scala compiler programs compiled by Scala Native closely match the behavior of programs compiled by the Scala compiler. First, we introduce NIR, an intermediate representation designed with ahead-of-time compilation in mind. NIR represents programs in the single-static assignment form and has support for object-oriented features such as virtual dispatch and multiple inheritance. This representation is a key enabler of our compilation and optimization pipeline. Secondly, we present Interflow, a link-time optimizer that takes advantage of the closed-world assumption to optimize the whole program at once. Our optimizer employs a number of techniques including partial evaluation, allocation sinking, and method duplication. The combination of these techniques allows Scala Native to outperform HotSpot on the majority of our benchmarks.
Suction Flows Generated by the Carnivorous Bladderwort Utricularia—Comparing Experiments with Mechanical and Mathematical Models

Suction feeding is a well-understood feeding mode among macroscopic aquatic organisms. The little we know about small suction feeders from larval fish suggests that small suction feeders are not effective. Yet bladderworts, an aquatic carnivorous plant with microscopic underwater traps, have strong suction performances despite having the same mouth size as that of fish larvae. Previous experimental studies of bladderwort suction feeding have focused on the solid mechanics of the trap door’s opening mechanism rather than the mechanics of fluid flow. As flows are difficult to study in small suction feeders due to their small size and brief event durations, we combine flow visualization on bladderwort traps with measurements on a mechanical, dynamically scaled model of a suction feeder. We find that bladderwort traps generate flows that are more similar to the inertia-dominated flows of adult fish than the viscosity-dominated flows of larval fish. Our data further suggest that axial flow transects through suction flow fields, often used in biological studies to characterize suction flows, are less diagnostic of the relative contribution of inertia versus viscosity than transverse transects.
EVALUATION OF BIOACTIVE COMPONENTS AND ANTIOXIDANT ACTIVITY OF VERNONIA ELAEAGNIFOLIA DC. (ASTERACEAE) IN GLYCOPHYTIC AND HALOPHYTIC CONDITIONS

Objective: The investigate some of the antioxidant activities and bioactive potentials of Vernonia elaeagnifolia grown hydroponically in glycophytic and halophytic conditions. Methods: Plants were grown in Hoagland solution and subjected to (Sodium chloride (NaCl) treatments. Plants cultivated without salt stress served as the control. The phytochemical analysis was done with the help of Gas Chromatography-Mass Spectrometry (GC-MS) and antioxidants were analyzed following standard procedures using UV-Visible Spectrophotometer. Results: Significant changes were observed in the presence of antioxidants like superoxide dismutase (SOD), catalase (CAT), guaiacol peroxidase (GPX), ascorbate peroxidase (APX), total polyphenols, proline and ascorbic acid. GPX and proline proved to be the major components in imparting salinity stress tolerance. The control showed the presence of 23 bioactive components while the treatment contained 19 components. Conclusion: The study thus provides information regarding the place of collection of the particular plant. Glycophytic conditions prove to be the best choice in terms of bioactive components and fatty acid contents. The investigations reveal that the plant contains several bioactive components and antioxidants, which prove it as a promising plant for developing potential drugs.
The Relationship Between Generalized Joint Hypermobility and Cervical Disc Degeneration, Neck Pain: A Multidisciplinary Clinical Study

Generalized joint hypermobility (GJH) is an observed phenomenon that may be inherited or very rarely acquired, which is defined as the ability to move the synovial joints beyond their normal range of motion (ROM). [1–3] Although its prevalence varies according to gender, age, and racial characteristics, it reaches to 15% in adults and 30% in childhood. [1,4] The Beighton scoring system (Annex 1) is used to detect GJH. [5,6] Cases with a score of ≥4 according to this scoring system are classified as hypermobile, and these criteria can be determined by five simple maneuvers that take a maximum of 1 min for physicians to perform. [7,8] Hypermobility (HM) plays an important role because of comorbid chronic pain complaints, premature osteoarthrosis, osteoporosis, and vascular and spinal disorders (scoliosis, spondylosis, and spondylolisthesis), and it may be overlooked especially when not searched for. [8,9]
Binarizing Weights Wisely for Edge Intelligence: Guide for Partial Binarization of Deconvolution-Based Generators

This article explores the weight binarization of the deconvolution-based generator in a generative adversarial network (GAN) for memory saving and speedup of image construction on the edge. This article suggests that different from convolutional neural networks (including the discriminator) where all layers can be binarized, only some of the layers in the generator can be binarized without significant performance loss. Supported by theoretical analysis and verified by experiments, a direct metric based on the dimension of deconvolution operations is established, which can be used to quickly decide which layers in a generator can be binarized. Our results also indicate that both the generator and the discriminator should be binarized simultaneously for balanced competition and better performance during training. The experimental results on CelebA dataset with DCGAN and original loss functions suggest that directly applying state-of-the-art binarization techniques to all the layers of the generator will lead to <inline-formula> <tex-math notation="LaTeX">$2.83\times $ </tex-math></inline-formula> performance loss measured by sliced Wasserstein distance compared with the original generator, while applying them to selected layers only can yield up to <inline-formula> <tex-math notation="LaTeX">$25.81\times $ </tex-math></inline-formula> saving in memory consumption, and <inline-formula> <tex-math notation="LaTeX">$1.96\times $ </tex-math></inline-formula> and <inline-formula> <tex-math notation="LaTeX">$1.32\times $ </tex-math></inline-formula> speedup in inference and training, respectively, with little performance loss. Similar conclusions can also be drawn on other loss functions for different GANs.
RANS Simulation of Local Strong Sandstorms Induced by a Cold Pool with Vorticity

Local strong sandstorms (LSSs) in northwestern China often occur suddenly in tens of minutes during the late afternoon and by dusk. Observations and theoretical studies have shown the trigger role of cold-air pools over desert areas for the occurrence of LSS. In this study, a numerical heat convection model was established to simulate an LSS that was induced by a single cold pool with vertical helicity to study the evolution process. The Reynolds averaged Navier–Stokes (RANS) method was used for the numerical calculation to illustrate different stages of the evolution process of an LSS. Results show that after the intrusion of a cold pool into the upper region of the surface convective mixing layer, descending of the cold air would lead to the downward transport of vorticity, enabling thermal convection cells in the mixing layer to become swirling convection cells. After LSS is fully developed, there occurs many subvortices (secondary vortices) in the convection field. The velocity at different altitudes over selected positions in the calculation domain is consistent with the "lobe" shape of an LSS. The secondary vortices cause quick and huge energy dissipation and the decay of the LSS. These results are consistent with observations and indicate the crucial effect of convection cells structure in the mixing layer and the cold pool in the upper layer on the formation of LSS.
Predicting completion of massive open online course (MOOC) assignments from video viewing behavior

ABSTRACT Predicting student performance in Massive Open Online Courses (MOOCs) is important to aid in retention efforts. Researchers have demonstrated that video watching features can be used to accurately predict student test performance on video quizzes employing neural networks to predict video test grades from viewing behavior including video searching (ff, rw, pause), replays, stop, and start. Deep learning neural networks are susceptible to overfitting with low data and higher dimensions; hence, we compare various commonly used classification algorithms including logistic regression and demonstrate similar or higher rates of prediction. However, using a path analysis approach we find that the features collectively explain only a small to moderate amount of variance in assignment completion, which suggests that other factors than video-viewing behavior influence assignment completion such as student goal motivation and student self-regulation. Overall, our findings highlight the important contribution of active searching and repeated viewing to successful assignment completion in a MOOC course. Predictive models based on user interactions with the MOOC platform can help target course retention strategies to increase MOOC completion where retention is abysmally low and help to target video viewing strategies to optimize teaching and learning platform functionality using adaptive agents.
Correlation of Allred Score with Tumor Behavior in Breast Cancer Patients Referred to Shahid-Mohammadi Hospital From 2010 to 2017

Background: Breast cancer is one of the most common malignancies in women around the world, which makes it essential to identify the behavior of tumors regarding cost-effectiveness and highly diagnostic methods. Objectives: The aim of this study was to determine the relationship between Allred score and tumor behavior in breast cancer patients. Methods: This study was performed on 100 patients with breast cancer. The following data were obtained for each participant: Patient satisfaction and demographic data, tumor size, tumor grade, lymph node involvement and histology of tumor, and Allred score. Chi-square, T student and analysis of variance (ANOVA) tests were used to compare the data. Results: The results of this study showed that Allred score based on PR and ER had a reverse and significant correlation with tumor size (P < 0.05). On the other hand, Allred negative findings were found to be higher in patients with lymph nodes involvement (P < 0.05). Conclusions: Considering the benefits and potentials of Allred score based on PR and ER in detecting tumor behavior and according to the high prevalence of breast cancer, it is suggested for the results of this study to be provided to specialists from different health centers to improve the correct prediction of tumor behavior.
The Effects of Workplace Safety Climate on Organizational Identification and Job Satisfaction Perceptions in Hotel Kitchens

In this study, it is aimed to investigate whether workplace safety climate has an effect on organizational identification and job satisfaction perceptions of hotel employees. The data used in the study were obtained from 205 employees in 2019 with a web-based questionnaire prepared for kitchen employees of 4 and 5 star hotel establishments in Ankara. By means of SPSS 25 program, t test, anova test and correlation analysis were conducted in order to determine the relationships between variables, the effects of the variables on each other, and the effect of workplace safety climate on organizational identification and job satisfaction perceptions. According to the results of correlation analysis; with organizational identification and job satisfaction of workplace safety climate; organizational identification with workplace safety climate and job satisfaction; job satisfaction is also found to have positive relationships between workplace security climate and organizational identification.
The Association Between Traditional Masculinity Ideology and Predictors of Military to Civilian Transition Among Veteran Men

Although there is ample evidence that endorsement of traditional masculinity ideology may negatively affect veteran men’s military to civilian transition, it remains unclear which specific facets of traditional masculinity are most likely to impede successful transition to civilian life. To better understand the association between traditional masculinity ideology and veteran transition, this study sought to examine the relationship between five facets of traditional masculinity ideology (restrictive emotionality, avoidance of femininity, toughness, dominance, and self-reliance) and four factors associated with difficult veteran transition (posttraumatic stress disorder [PTSD], depression, perceived social support, and alcohol-related problems) in (N = 289) veteran men. Results indicate that restrictive emotionality was the most significant contributing facet of traditional masculinity ideology to PTSD, depression, and perceived social support, whereas avoidance of femininity was the masculinity facet most significantly associated with alcohol-related problems. Theoretical and clinical implications are discussed.
Immunophenotyping Oral Amyloidosis for the Precise Identification of the Biochemical Forms: A Retrospective Study

Amyloidosis refers to a group of systemic and localized disorders associated with the accumulation of misfolded protein aggregates called amyloids in different parts of the body. Owing to the existence of multiple forms of amyloids with similar tertiary structures, precise identification of their biochemical form is critical for correct therapy. This retrospective study aimed to determine whether typing of oral amyloid deposits can help diagnose a serious systemic condition in the early phase of the disease All histopathologically confirmed cases of amyloidosis managed over a 14-year period (January 1, 1997 to December 31, 2011) were retrieved for analysis. Two board-certified oral and maxillofacial pathologists reviewed the histopathological findings of amyloidosis on the basis of its classic Congo red staining characteristics. This was followed by immunohistochemical analysis of biopsy samples using a panel of antibodies specific for different forms of amyloidosis. The most common location of amyloidosis was the tongue, and women were more commonly affected than men. The patient age ranged from 11 to 83 years (average 59.3 years). In patient 9, light-chain and pre-albumin (transthyretin) antibodies were related to arthritis and senile amyloidosis, respectively. The biopsy sample of patient 10, who was reported to have multiple myeloma, was positive for light chains and β2 microglobulin. All other samples exhibited localized (solitary) amyloidosis. Histological analysis coupled with immunostaining with a panel of specific antibodies might assist in identifying early systemic amyloidosis in patients with localized oral forms of the disease.
Epidemiology of Epilepsy in Korea

proximately 50 million people of all ages worldwide. Epidemiological studies provide useful data both for primary prevention and for setting public health and health care priorities, as well as furnishing information on measures that can be taken for early detection and treatment. However, only a few epidemiological studies of epilepsy have been conducted in Korea. In this review, those studies and related issues regarding epidemiological research on epilepsy are discussed.
Seismological Observatory Software: 30 Yr of SEISAN

The SEISAN software package for processing of earthquake data has been in use for 30 yr. SEISAN is a collection of programs that help to carry out tasks from the basic processing at a seismological observatory to more advanced seismological research. During its history, the software has been adopted to different hardware and operating systems. However, the core of the software with a folder- and files-based database and event-based processing has remained stable. The main focus in the design and development of the software has been the efficiency in data processing for the user. The software comes with manual, tutorial, and training exercises. This together with regular training activities has made SEISAN a useful tool for many observatories around the world.
Perceptions of tourism: a study of residents' attitudes towards tourism in the city of Girona

Socio-cultural impacts of tourism have been widely researched within a social exchange theoretical framework, yet it seems that this theory could be neglecting those more emotional elements, which at the same time could be considered key to understand how tourism affects the society. Therefore, the purpose of this paper is to look at the social exchange theory (SET) from a different perspective and focus on those less rational influencing factors that could be shaping residents’ attitudes towards tourism. ,Based on six main constructs, a quantitative survey-based research is developed in the small city of Girona with the purpose to broaden the versality of the theory, with the support of in-depth exploratory interviews. Thus, an exhaustive study of the influences that attachment to communities, involvement in the tourism industry and personal benefits derived from tourism could have on residents’ perceptions is developed. ,This paper suggests that those smaller tourism destinations might mirror themselves in those close big tourism destinations and thus residents’ opinions and attitudes seem to be influenced by the situations lived in these larger tourism destinations. Moreover, this paper stresses on the importance of interactions and relationships between tourists and residents to boost personal benefits from tourism. Finally, results show how those attached citizens tend to support tourism development, which could be explained by the proudness they feel when others value what for them is home. ,This paper contributes to the current understanding of attitudes towards tourism within the SET framework, especially relating to covering those more emotional elements of social interactions. Moreover, there seems to be a gap in current research relating to small urban destinations that is aimed to be covered in this research.
Driver Takeover Performance and Monitoring Behavior with Driving Automation at System-Limit versus System-Malfunction Failures

Today’s vehicles are becoming highly automated, however, if the automation fails, drivers must take over control of the vehicle. Automation may fail as a result of known system limits (system-limit failure) or of malfunctions that are unforeseen by system designers (system-malfunction failure). The aim of this research was to quantify the differences between how these two failure types influence driver takeover performance and monitoring behaviors. In a simulator with SAE Level 2 driving automation, 18 drivers experienced both a system-limit and system-malfunction failure while engaging in a secondary task. Results show that drivers put their hands on the wheel 0.62 s sooner and took over 0.51 s faster for the system-limit failure compared with the system-malfunction failure. Eye tracking data revealed that the percent of time looking at the secondary task display was 12.7% lower and the percent of time looking at the roadway was 11.2% higher before the system-limit failure compared with before the system-malfunction failure. Given that takeover performance and monitoring behavior differ significantly based on failure type, a distinction should be made in the literature between system-limit and system-malfunction failures, and comparisons between previous studies using these failures should not be done without considering this distinction. Furthermore, as SAE Level 2 vehicles are currently available to consumers, efforts should be focused on supporting drivers’ mental models of automated systems, so that drivers are able to successfully predict system-limit failures.