Miracle-dz/UniFAR-FTUs huggingface dataset:
Use of the Data Mining Clustering Technique to Identify Student Behaviors in Virtual Environments

Today, universities around the world are incorporating virtual platforms in order to bring their academic offer closer and increase their coverage. Under this context new schemes emerge that incorporate elements focused on meeting the needs of students in these environments. Although it is true that each student has a different learning style [1], according to different studies and models, it is also true that the development of materials within virtual learning environments must be addressed in these schemes [2]. Under this new teaching context, new questions emerge about the use that the students make of the new Information and Communication technologies that are included within the different platforms that implement the Universities for such effect [3]. This research focuses on the application of data mining algorithms, using the Clustering technique on the Weka tool, to describe the pattern of behavior of university students in virtual environments, specifically on the Moodle Platform. In this way, when knowing the different patterns of behavior, improvement projects can be implemented on the materials and activities of the virtual environment that match the learning styles predicted.
Sulphate supply and its regulation of transport in roots of a tropical legume Macroptilium atropurpureum cv. Sirato

During a period of sulphate deprivation, roots of Macroptilium atropurpureum responded by increasing their uptake capacity at the plasma membrane. This effect was apparent both in intact plants and in tissues excised prior to uptake. In experiments using excised root systems previously labelled with 35 SO 4 2− , the rate of tracer transport to the xylem was much greater in roots subsequently deprived of external sulphate than in those supplied with unlabelled sulphate. Removing the external sulphate supply also greatly reduced the loss of sulphate to the external solution. Additionally, compartmental analysis of tracer exchange kinetics showed that the flux of sulphate from the cytoplasm to the xylem (Φ cx ) was much larger than that from the vacuole to the cytoplasm (Φ vc ) in roots supplied with 0.25 mol m −3 SO 4 2− . Therefore, once the external sulphate supply is removed, the flux of sulphate out of the cytoplasm (to the xylem) is likely to be much greater than the flux into the cytoplasm (from the vacuole), especially if the xylem flux is increased. Thus, even though the total sulphate content of roots fell by less than half during the first 24 h of sulphur deprivation the cytoplasmic concentration may have fallen substantially, resulting in a 3-fold increase in the uptake capacity of intact roots. The results are discussed in relation to the control of sulphate transport across the plasmalemma and the redistribution of sulphur during sulphur stress
Information fusion in multi-task Gaussian processes

This paper evaluates heterogeneous information fusion using multi-task Gaussian processes in the context of geological resource modeling. Specifically, it empirically demonstrates that information integration across heterogeneous information sources leads to superior estimates of all the quantities being modeled, compared to modeling them individually. Multi-task Gaussian processes provide a powerful approach for simultaneous modeling of multiple quantities of interest while taking correlations between these quantities into consideration. Experiments are performed on large scale real sensor data.
EXPERIMENTAL ANALYSIS BASED ON OPTICAL MODEL AND ELECTROMAGNETIC PROPERTIES OF MULTILAYER ABSORBERS

1Instituto Tecnológico de Aeronáutica, ITA, Praça Mal. do Ar Eduardo Gomes, 50, 12228-904 São José dos Campos-SP, Brazil 2Comando de Comunicações e Guerra Eletrônica do Exército, Estrada Parque do Contorno, Rodovia DF001, km 05 Setor Taquari Lago Norte, 71559-902 – Brasília-DF, Brazil 3Instituto Superior de Educação de Brasília, Asa Sul SGAS Quadra 613/614 70.200-730 – Brasília – DF, Brazil 4Instituto de Ciência e Tecnologia, ICT/UNIFESP, Talim, 330, 12231-280 São José dos Campos-SP, Brazil
BTHYDRA+: Towards a Comprehensive Model to Conduct Cross-project Defect Prediction

Cross-project defect prediction (CPDP) is a field of study where researchers need to build a universal model by using within-project data to predict defects on other projects. However, variations in the distribution of source and target projects have an influence on the performance of classifiers. To enable effective cross-project defect prediction, we propose a comprehensive model containing data preprocessing and classifier transferring to construct a better classification space and strengthen the performance of classifiers. In preprocessing step, one baseline is calculated for every dataset from its non-defective samples based on the distance to all other non-defective samples and the data is transformed by using rank function. Genetic algorithm and ensemble learning are selected as the way in transferring step to extract effective representation from source projects and boost the capability of weak classifiers. We use Naive Bayes, Support Vector Machine and Classification and Regression Trees as classifiers and apply this model on five open resource projects (one Apache and four Eclipse projects) and NASA MDP dataset. Selecting accuracy as fitness in genetic algorithm improves the performance of classification. The model we proposed yields similar results and obtains higher precision comparing the within-project models. Meanwhile, it obtains better performance than the state-of-the-art methods on cross-project defect prediction. These results show that our model provides an opportunity to training classifiers by using more samples from different projects.
Andreas Jansen

The study has to clear objectives. The first aim is to explain the still existing variances in the labour market participation of older people in Europe by broadening the set of possible explanations by a cultural construct, namely the specific ‘work-retirement-culture' of a country. Subsequently it will be analysed if the work-retirement-culture functions as a barrier against reforms of the pension system that might be reasonable from a pure economic perspective, but are entirely contrary to the respective work/retirement culture. With regard to the first objective, the results give some indications that the work/retirement culture could indeed be a further piece of the puzzle to explain differences in the labour market participation of older people in Europe since an early-exit culture can primarily be observed in countries with a comparably low labour market participation of older people aged between 55 and 64 years, while the opposite is true for countries showing an employment-oriented work/retirement culture. In addition the analysis of the change and persistence of the institutional setting has shown some evidence that the work/retirement culture at least partly functions as a barrier or promoter in pension reforms.
A Deep Learning Framework for Tactile Recognition of Known as Well as Novel Objects

This paper addresses the recognition of daily-life objects by a robot equipped with tactile sensors. The main contribution is a deep learning framework that can recognize objects already touched as well as objects never touched before. To this end, we train a deconvolutional neural network that generates synthetic tactile data for novel classes. Then, we use both these synthetic data and the real data collected by touching objects, to train a convolutional neural network to recognize both known (trained) objects and novel objects. Furthermore, we propose a method for integrating newly encountered data into novel classes. Finally, we evaluate the framework using the largest available dataset of tactile objects descriptions.
Comparing the Urine Ketone Strip Test and the Handheld Ketone Meter to Diagnose Ketosis in Early Lactation Dairy Cows

Ketosis is a common metabolic disease in fresh dairy cows. Clinical and subclinical ketosis (SCK) can cause reduced milk yield, decreased milk protein, reduced reproductive capacity, and increased risk of displaced abomasum. Usually, diagnosing ketosis is performed by measuring acetoacetate or BHBA levels in the blood, urine, or milk samples. Measuring BHBA in serum or plasma is considered the gold standard diagnostic test for subclinical ketosis, because this method has stability, but the price for ketone strips is approximately $0.08/strip while the price for the electronic BHBA measuring system is approximately $1.00. UF/IFAS researchers conducted a study to compare the two, using 72 Holstein cows between 14–40 days in milk from three dairy farms in north-central Florida with 450–800 lactating dairy cows. The key finding for this experiment is that no difference exists in BHBA concentration between cows that had a trace or small in the ketone strip reading. This 3-page fact sheet was written by Klibs N. Galvão, Achilles Vieira Neto, Gustavo Peña, Joao Bittar, and Lucas Ibarbia, and published by the UF Department of Veterinary Medicine-Large Animal Clinical Sciences, October 2012. VM186/VM186: Comparing the Urine Ketone Strip Test and the Handheld Ketone Meter to Diagnose Ketosis in Early Lactation Dairy Cows (ufl.edu)
High-Frequency Shoot Regeneration of Various Cultivars of Banana (Musa sp.)

ABSTRACT An efficient, simple, and rapid regeneration system was established for bananas (Musa sp.) using sections of corm containing intercalary meristematic tissues as explants. Six different cultivars of banana (‘Mpologoma’, ‘Nakitembe’, ‘Mbwazirume’, ‘Pisang awak’, ‘Sukali ndiizi’, and ‘FHIA-17’) with diverse genetic constitution and ploidy levels were regenerated on Murashige and Skoog (MS) medium supplemented with 5 mgl−1 of 6-benzylaminopurine. All the cultivars showed relatively high regeneration efficiency. About 93–97% of the explants regenerated, producing, on average, 12–13 shoots from whole section and 16–19 shoots in total from quarter pieces of each section. Regeneration from intercalary meristematic tissues offers a simple, efficient method for transformation of a broad range of banana cultivars, including East African Highland bananas.
Deep Reinforcement Learning for Subpixel Neural Tracking

Automatically tracing elongated structures, such as axons and blood vessels, is a challenging problem in the field of biomedical imaging, but one with many downstream applications. Real, labelled data is sparse, and existing algorithms either lack robustness to different datasets, or otherwise require significant manual tuning. Here, we instead learn a tracking algorithm in a synthetic environment, and apply it to tracing axons. To do so, we formulate tracking as a reinforcement learning problem, and apply deep reinforcement learning techniques with a continuous action space to learn how to track at the subpixel level. We train our model on simple synthetic data and test it on mouse cortical two-photon microscopy images. Despite the domain gap, our model approaches the performance of a heavily engineered tracker from a standard analysis suite for neuronal microscopy. We show that fine-tuning on real data improves performance, allowing better transfer when real labelled data is available. Finally, we demonstrate that our model’s uncertainty measure—a feature lacking in hand-engineered trackers—corresponds with how well it tracks the structure.
A Survey and Tutorial on the Possible Applications and Challenges of Wearable Visual Lifeloggers.

Advances in manufacture of miniaturized low-power embedded systems are paving the way for ultralight-weight wearable cameras that can be used for visual lifelogging of minute details of people’s daily lives. The ability of wearable cameras to continuously capture the ﬁrst person viewpoint with minimal user interaction, have made them very attractive in many application domains. Although today the wearable cameras are available and useful, but they are not widely used and accepted due to various challenges such as privacy concerns and some technical limitations. In this paper, possible industrial, medical, martial, educational, personal and media applications of wearable cameras are highlighted. The main challenges in realizing the full potential of wearable cameras are outlined and current state-of-the-art proposals for addressing these challenges are reviewed.
Study of technologies implemented in the operation of SF6 switches

This research aims to evaluate the trends in the publication of papers on issues related to power circuit breakers, aimed at the technologies implemented, as well as those countries with higher level of publications, making a comparison between authors, research institutes, and a description of the last 10 years with more publications. All the information found in this report is compiled in bibliographic databases such as books of substation designs and research papers with a focus on electrical protection equipment and emphasis on high voltage switching devices. A technology research is conducted over the last ten years to analyze the state of the art of high voltage operating elements with respect to new technologies.
Quality Effects on User Preferences and Behaviorsin Mobile News Streaming

User behaviors are widely used as implicit feedbacks of user preferences in personalized information systems. In previous works and online applications, the user's click signals are used as positive feedback for ranking, recommendation, evaluation, etc. However, when users click on a piece of low-quality news, they are more likely to have negative experiences and different reading behaviors. Hence, the ignorance of the quality effects of news may lead to the misinterpretation of user behaviors as well as consequence studies. To address these issues, we conducted an in-depth user study in mobile news streaming scenario to investigate whether and how the quality of news may affect user preferences and user behaviors. Firstly, we verify that quality does affect user preferences, and low-quality news results in a lower preference. We further find that this effect varies with both interaction phases and user's interest in the topic of the news. Secondly, we inspect how users interact with low-quality news. Surprisingly, we find that users are more likely to click on low-quality news because of its high title persuasion. Moreover, users will read less and slower with fewer revisits and examinations while reading the low-quality news. Based on these quality effects we have discovered, we propose the Preference Behavior Quality (PBQ) probability model which incorporates the quality into traditional behavior-only implicit feedback. The significant improvement demonstrates that incorporating quality can help build implicit feedback. Since the importance and difficulty in collecting news quality, we further investigate how to identify it automatically. Based on point-wise and pair-wise distinguishing experiments, we show that user behaviors, especially reading ratio and dwell time, have high ability to identify news quality. Our research has comprehensively analyzed the effects of quality on user preferences and behaviors, and raised the awareness of item quality in interpreting user behaviors and estimating user preferences.
Place Deduplication with Embeddings

Thanks to the advancing mobile location services, people nowadays can post about places to share visiting experience on-the-go. A large place graph not only helps users explore interesting destinations, but also provides opportunities for understanding and modeling the real world. To improve coverage and flexibility of the place graph, many platforms import places data from multiple sources, which unfortunately leads to the emergence of numerous duplicated places that severely hinder subsequent location-related services. In this work, we take the anonymous place graph from Facebook as an example to systematically study the problem of place deduplication: We carefully formulate the problem, study its connections to various related tasks that lead to several promising basic models, and arrive at a systematic two-step data-driven pipeline based on place embedding with multiple novel techniques that works significantly better than the state-of-the-art.
Inter-municipal facility location-routing model

The planning of efficient and process-oriented inter-municipal street maintenance operations involve several decision making processes. Road maintenance for municipalities is an important activity to deliver value for money for the inhabitants and therefore has to be planned carefully. Nowadays Swiss municipalities have to deal with inefficient structures regarding the operational street maintenance in terms of cost, resources and labour which lead to high organizational costs. This paper is concerned with the planning of optimized multi-municipal facility locations in the field of operational street maintenance. The location of operation centres is one of the most important strategic decisions for municipalities performing inter-municipal street maintenance operations. Especially in times of declining public income, Swiss communities are trying to improve their efficiencies of operational street maintenance. In cooperation with the Swiss Federal Roads Authority (ASTRA), the Chair of Construction Process and Enterprise Management at the Institute of Construction and Infrastructure Management at ETH Zurich is developing an inter-municipal facility location-routing model in the field of operational road maintenance. It serves as a decisionmaking basis for street owners to improve the efficiency of operational road maintenance processes. This paper presents an inter-municipal facility location-routing and shows possible algorithms for optimizing global costs. Localization decisions present a very complex decision making problem that involve considerations of multiple criteria such as the minimization of build-up and installation cost of a new operation centre, transportation cost as well as an ideal availability to the municipal road network. The constructivist research approach will be applied to the development of the inter-municipal facility location-routing model. This research approach follows the hermeneutic research paradigm and aims to structure new socio-technical systems based on an intended input-output effect. The holistic facility location-routing model forms a basis for systematically developing operational street maintenance strategies. The aim is to ensure a high standard of street network quality, create a tool for local authorities, enabling them to cope more easily with challenging economic aspects and to provide good value to the customer and road users.
Effect of thimerosal on Ca2+ movement and apoptosis in PC3 prostate cancer cells

The present study evaluated the effects of thimerosal, a vaccine preservative, on cytosolic free Ca2+ concentrations ([Ca2+]i) in human prostate cancer cells (PC3). Thimerosal (10–200 µM) increased [Ca2+]i in a concentration‐dependent manner. The Ca2+ signal was reduced partly by removing extracellular Ca2+. Thimerosal‐induced Ca2+ influx was inhibited by econazole, SKF963656, the phospholipase A2 inhibitor aristolochic acid, and protein kinase C modulators [phorbol 12‐myristate 13‐acetate (PMA) and GF109203X]. In Ca2+‐free medium, a 200‐µM thimerosal‐induced [Ca2+]i rise was partly inhibited after pretreatment with 2,5‐di‐tert‐butylhydroquinone (BHQ) (an endoplasmic reticulum Ca2+ pump inhibitor). Thimerosal at 1–7 µM induced cell death in a concentration‐dependent manner that was not reversed when cytosolic Ca2+ was chelated with 1,2‐bis(2‐aminophenoxy)ethane‐N,N,N′,N′‐tetraacetic acid (BAPTA). Propidium iodide staining suggests that apoptosis played a role in the death. Collectively, in PC3 cells, thimerosal induced [Ca2+]i rise by causing Ca2+ release from the endoplasmic reticulum and Ca2+ influx via store‐operated Ca2+ channels in a manner regulated by protein kinase C and phospholipase A2. Thimerosal also induced cell death in a Ca2+‐independent apoptotic manner. Drug Dev Res 72: 330–336, 2011. © 2011 Wiley‐Liss, Inc.
Surface Acoustic Wave Resonators Using Lithium Niobate on Silicon Carbide Platform

This work demonstrates a group of shear horizontal (SHO) mode surface acoustic wave (SAW) resonators using Lithium Niobate (LiNbO3) thin films on Silicon Carbide (SiC) substrates. The fabricated resonator has demonstrated a large effective electro-mechanical coupling ($kt^{2}$) of 26.6% and a high-quality factor (Bode-Q) of 1092, hence resulting in a high figure of merit (FoM= $kt^{2}$ ·Bode-Q) of 290 at 1.90 GHz. Additionally, these fabricated resonators show scalable resonances from 1.71 GHz to 3.17 GHz, and impedance ratios between 55.9 dB and 67.5 dB.
RECURSIVE LEAST SQUARES ALGORITHM FOR ADAPTIVE TRANSVERSAL EQUALIZATION OF LINEAR DISPERSIVE COMMUNICATION CHANNEL

This paper is intended to analyse the performance, the rate of convergence, selection of proper filter order number, misadjustment, sensitivity to Eigenvalues spread, and computational requirement of the Recursive Least Squares (RLS) algorithm, which is one of the well-known effective algorithms in the field of adaptive filters. Finally, the effect of decision feedback equalizer to improve the system is presented. The RLS algorithm repeatedly minimizes a weighted linear least squares value of the error and therefore, it is known for its excellent high convergence performance in time varying environments. The drawback of this algorithm is the computational complexity and stability problem. The simulation work related to this adaptive filter is performed by MATLAB software.
Overlaps in habitat use of fishes between a seagrass bed and adjacent coral and sand areas at Amitori Bay, Iriomote Island, Japan: Importance of the seagrass bed as juvenile habitat

: To clarify faunal overlap between a seagrass bed and adjacent coral and sand areas, and the number of reef fishes utilizing the seagrass bed as juvenile habitat, visual censuses were conducted at Amitori Bay, Iriomote Island, Japan. The numbers of species and individuals of fishes were significantly higher in the coral area than in the seagrass bed and sand area. Cluster and ordination analyses based on the number of individuals of each species demonstrated that the fish assemblage structure differed among the three habitats in each season, but with some overlaps. Approximately half the seagrass bed fishes occurred in the adjacent coral area (coral–seagrass species). Dominant species of coral–seagrass species utilized the seagrass bed as an important juvenile habitat. Thus, some overlaps in habitat use were present between the seagrass bed and adjacent coral area. Despite such overlaps, however, coral–seagrass species accounted for only approximately 15% of coral reef fishes overall, indicating that most of the latter hardly utilize the seagrass bed directly in the study area.
Opera-oriented character relations extraction for role interaction and behaviour Understanding: a deep learning approach

ABSTRACT There are a great number of complex relations among different characters in an opera. Retrieving such relations is crucial for performers and audience to accurately understand the features and behaviour of roles. Aiming to automatically extract relations among characters in an opera, in this paper we propose an effective method that can extract character relations from opera scripts. Firstly, we construct a uniform reasoning framework for opera scripts. Based on this model, we propose a deep syntax-parsing method to detect character relations from opera scripts. After that, we propose a new deep learning approach called SL-Bi-LSTM-CRF to extract the objects involved in character relations. The proposed SL-Bi-LSTM-CRF algorithm is a sentence-level relation extraction algorithm based on the Bi-directional LSTM with a CRF layer. With this mechanism, we are able to get a detailed description for character relations. We conduct experiments on a real dataset of opera scripts. The experimental results in terms of precision, recall, and F-score suggest the effectiveness of our proposal.