Miracle-dz/UniFAR-FTUs huggingface dataset:
ON THE PREDICTIVE POWER OF META – FEATURES

The demand for performing data analysis is steadily rising. As a consequence, people of different profiles (i.e., nonexperienced users) have started to analyze their data. However, this is challenging for them. A key step that poses difficulties and determines the success of the analysis is data mining (model/algorithm selection problem). Meta-learning is a technique used for assisting non-expert users in this step. The effectiveness of meta-learning is, however, largely dependent on the description/characterization of datasets (i.e., meta-features used for meta-learning). There is a need for improving the effectiveness of meta-learning by identifying and designing more predictive meta-features. In this work, we use a method from exploratory factor analysis to study the predictive power of different meta-features collected in OpenML, which is a collaborative machine learning platform that is designed to store and organize meta-data about datasets, data mining algorithms, models and their evaluations. We first use the method to extract latent features, which are abstract concepts that group together meta-features with common characteristics. Then, we study and visualize the relationship of the latent features with three different performance measures of four classification algorithms on hundreds of datasets available in OpenML, and we select the latent features with the highest predictive power. Finally, we use the selected latent features to perform meta-learning and we show that our method improves the meta-learning process. Furthermore, we design an easy to use application for retrieving different meta-data from OpenML as the biggest source of data in this domain.
Achieving the optimal performance of the CMS ECAL in Run II

Many physics analyses using the Compact Muon Solenoid (CMS) detector at the LHC require accurate, high resolution electron and photon energy measurements. Particularly important are decays of the Higgs boson resulting in electromagnetic particles in the final state. Di-photon events in CMS are also a very important channel in the search for Higgs boson production in association with other particles or in the search for possible new resonances of higher mass. The requirement for high performance electromagnetic calorimetry therefore remains high during LHC Run II. Following the excellent performance achieved in Run~I at a center of mass energy of 7 and 8 TeV, the CMS electromagnetic calorimeter (ECAL) started operating at the LHC in Spring 2015 with proton-proton collisions at 13 TeV center-of-mass energy. The instantaneous luminosity delivered by the LHC during Run~II is expected to exceed the levels achieved in Run I, using 25 ns bunch spacing. The average number of concurrent proton-proton collisions per bunch-crossing (pileup) is expected to reach up to 40 interactions in 2016. These high pileup levels necessitate a retuning of the ECAL readout and trigger thresholds and reconstruction algorithms, to maintain the best possible performance in these more challenging conditions. The energy response of the detector must be precisely calibrated and monitored to achieve and maintain the excellent performance obtained in Run I in terms of energy scale and resolution. A dedicated calibration of each detector channel is performed with physics events exploiting electrons from W and Z boson decays, photons from $\pi^0$/$\eta$ decays and from the azimuthally symmetrical energy distribution of minimum bias events. This paper describes the new reconstruction algorithm and calibration strategies that we have implemented to maintain the excellent performance of the CMS ECAL throughout Run II. We will show performance results from the 2015 and 2016 data taking periods and provide an outlook on the expected Run II performance in the years to come.
Correlation-Picture Approach to Open-Quantum-System Dynamics

We introduce a new dynamical picture, referred to as correlation picture,' which connects a correlated state to its uncorrelated counterpart. Using this picture allows us to derive an exact dynamical equation for a general open-system dynamics with system--environment correlations included. This exact dynamics is in the form of a Lindblad-like equation even in the presence of initial system-environment correlations. For explicit calculations, we also develop a weak-correlation expansion formalism that allows us to perform systematic perturbative approximations. This expansion provides approximate master equations which can feature advantages over existing weak-coupling techniques. As a special case, we derive a Markovian master equation, which is different from existing approaches. We compare our equations with corresponding standard weak-coupling equations by two examples, where our correlation picture formalism is more accurate, or at least as accurate as weak-coupling equations.
Simulation of qubit quantum circuits via Pauli propagation

We present novel algorithms to estimate outcomes for qubit quantum circuits. Notably, these methods can simulate a Clifford circuit in linear time without ever writing down stabilizer states explicitly. These algorithms outperform previous noisy near-Clifford techniques for most circuits. We identify a large class of input states that can be efficiently simulated despite not being stabilizer states. The algorithms leverage probability distributions constructed from Bloch vectors, paralleling previously known algorithms that use the discrete Wigner function for qutrits.
Diagnostic classification and symbolic guidance to understand and improve recurrent neural networks

This paper describes a search through a variety of methods to inspect and understand the internal dynamics of gated recurrent neural networks, using a task focusing on a key feature of language: hierarchical compositionality of meaning. We study both gated recurrent units and long short term memory networks with a technique called diagnostic classification, in which a simple neural meta-model is trained to qualitatively evaluate hypotheses about the information that is encoded in the hidden state of a trained network. Using this method, we analyse the hidden layer activations, but also the gates of trained networks. We explore the potential limits of diagnostic classification using not only the accuracy of the resulting diagnostic classifiers, but also studying their weights to understand where and how information is encoded. As a result, we develop a detailed understanding of the computations implemented by the networks to execute their task, which we then utilise to improve their performance with a new training regime we call symbolic guidance. This regime uses symbolically generated targets that are specifically designed to leverage our knowledge about the inherent bias of the networks and leads to a clear improvement against the best previous model.
Accuracy of 12h-Petrifilm™-plates as a rapid on-farm test for evidence-based mastitis therapy on a dairy farm in Germany

Antibiotic resistance is a highly discussed issue in society. The use of antibiotics in livestock husbandry is critically viewed. As a result, the European commission issued guidelines for the prudent use of antimicrobial agents in veterinary medicine in 2015 (EU 2015/C 299/04). Thus, alternative approaches for treating cows in the future are necessary. In particular, the treatment of mastitis, the most frequent disease in the dairy industry, causes a high use of antibiotics. Implementing an on-farm test to assign mastitis pathogens to classes of pathogens (Gram-positive, Gram-negative, no bacterial growth) before treatment decisions are made provides the basis for an evidence-based mastitis therapy concept. Rapid Aerobic Count plates and Rapid Coliform Count plates of 3M™ Petrifilm™ (3M™ Neuss, Germany) were used in combination as a 12h rapid on-farm test concept. The diagnostic sensitivity and specificity were evaluated in comparison to the standard laboratory examination. 129 mastitis milk samples from the quarters with clinical mastitis by a conventional dairy farm in Germany were used for evaluation. Results were examined 12 hours after inoculating the Petrifilm™-plates. The sensitivity for Gram-positive pathogens was 93.2%. For Gram-negative pathogens it was 88.9%. The specificity was 39.0% for Gram-positive pathogens and 97.5% for Gram-negative pathogens, respectively. To get good results, training the milking personnel in taking aseptic milk samples as well as inoculating and evaluating the test is inevitable. On the basis of the results the 12h-Petrifilm™ concept can serve as a basis for treatment decisions in the evidence-based mastitis therapy in dairy herds with a low percentage of infections with eukaryotic pathogens and can complement bacteriological culture.
Extractive Summarization with Very Deep Pretrained Language Model

Recent development of generative pretrained language models has been proven very successful on a wide range of NLP tasks, such as text classification, question answering, textual entailment and so on.In this work, we present a two-phase encoder decoder architecture based on Bidirectional Encoding Representation from Transformers(BERT) for extractive summarization task. We evaluated our model by both automatic metrics and human annotators, and demonstrated that the architecture achieves the stateof-the-art comparable result on large scale corpus - CNN/Daily Mail . As the best of our knowledge, this is the first work that applies BERT based architecture to a text summarization task and achieved the state-of-the-art comparable result.
Design of a Rise Support to be integrated in the HOBBIT Robot

The purpose of the thesis work is to analyze the possibility to integrate a sit-to-stand functionality into the HOBBIT service robot for elderly people while keeping the stability of the robot. A prototype with a knee support and a handle was used in combination with a motion capture system to capture joints angles and forces during the sit-to-stand movement. A skeletal model was created using the OpenSim software where data and a CAD model of the robot were imported and analyzed. Matlab was used to calculate the stability of the robot and optimize the positions of the knee support and handle. Finally, the prototype was tested with four elderly people. The forces necessary to rise up did not compromise the stability of the robot and the users found the prototype useful, comfortable and necessary.
Synthesis of ferrihydrite and feroxyhyte

Ferrihydrite and feroxyhyte were synthesized at room temperature from 0.1 M FeSO 4 . Ferrihydrite, with 6 to 7 diffraction lines, formed at pHs 5-11 in the presence of Si (Fe:Si = 10:1). The use of Ge, in place of Si, resulted in the same, with the same d-spacings of the diffraction peaks. This indicates that the Si or Ge is not in the structure of ferrihydrite, but forms Fe-O-Si (or Ge) at the periphery of «domain» of ferrihydrite. The presence of Si or Ge was a requisite for the formation of ferrihydrite, because their absence led, at the pHs investigated, to the formation of goethite or lepidocrocite
TITLE " Comparison of Two Measures of Type A Behavior in Childreno

ABSTRACT This study assessed the interchangeability of the Matthews Youth Test for Health (MYTH) and Hunter-Wolf A-B Rating Scale. Data from 25 elementary teachers and 300 o their students showed these scales to be weakly correlated, and the concordance of their A-B classifications to be only slightly above that expected by chance. Weak agreement was found even whe teachers and students rated the same Type behaviors, suggestin rk
THE TOURIST DEMAND FROM THE PERSPECTIVE OF THE MOTIVATION, ASSESSMENT AND SATISFACTION IN A SUN AND BEACH DESTINATION: THE MANTA CASE, ECUADOR

Conducting studies of motivation, evaluation and satisfaction of the demand of sun and beach tourism provides important information to adapt the products according to demand. The present study was conducted in situ in the city of Manta, Ecuador. Using a questionnaire, variant and bivariate statistical techniques were used to achieve the study objectives. The findings show that the main motivations of tourists are to rest, enjoy the beach and the sun, and enjoy the typical local gastronomy, which ratifies the main motivations in destinations with these characteristics. The most valuable aspects of the visit were the hospitality of the residents, the sun and the beach, and the restaurant service. The satisfaction of the destination is high, which shows the potential of this site for this type of tourism.
Influences of Salt Stress and Foliar Fertilizers on Growth , Chlorophyll and Carotenoids of Jojoba Plants

The response of growth and photosynthetic pigments of jojoba plants due to potassium sulphate (KS) and ammonium phosphate (AP) and salt stress was studied in a pot experiment which was conducted in the greenhouse of the National Research Centre, Dokki, Cairo, Egypt in the 2012 and 2013 summer season. The treatments of salinity were: irrigation by diluted seawater, 6000 and 3000 ppm and tap water (290 ppm) as a control, and fertilizers treatments were spraying of AP and KS in the rate of 1g/L more than distilled water as a control. Results revealed that increasing of salt concentration led to decrease the dry mass of stem, leaves, top and whole jojoba plant dry weight. Root dry mass which seemed to be without effect. Irrigation jojoba plants with water contains 6000 ppm decreased stem, leaves, top and whole plant dry weight by 4.9, 13.5, 0.3 and 1.6% compare with those irrigated by tap water. Top to root ratio decreased considerably with the increase of salts in the diluted seawater. Spraying plants by potassium fertilizer increased vegetative characters i.e. dry weight of root, stem, top and whole plant. Salt stress decreased chl.a, chl.b, total chlorophyll and chl.a+chl.b:carotenoids as the concentration of salts increased. The reverse was true in carotenoids concentrations, however, chl.b increased with moderate salt stress and tended to decrease with high salt levels but still more than the control. Application of AP showed the highest concentration of chl.a, chl.b and chl.a+chl.b as well as total carotenoids. On the opposite side, KS showed the lowest chl.a value and distilled water showed the lowest valus of chl.b and carotenoids. The highest ratios (Chl.a:chl.b and chl.a+chl.b:carotenoids) were obtained by distilled water spraying and the values resulted from spraying KS came in between.
AGRICULTURAL COMPETITIVENESS AND SUPPLY CHAIN INTEGRATION: SOUTH AFRICA, ARGENTINA AND AUSTRALIA

Abstract The international competitiveness of South African agricultural exports relative to those of Argentina and Australia is considered. Competitiveness was measured in terms of the Relative Comparative Advantage (RTA) using data from FAOSTAT 2002, while trade perspectives were examined using data from the World Trade Organisation and the Trade and Industrial Policy Strategies (TIPS) databases. The results of the RTA show that South Africa's agricultural food chains are marginally competitive internationally, whereas Argentina and Australia's agricultural food chains are internationally competitive. The analysis also shows that South Africa has managed to move up the value chain relative to Argentina and Australia. Nevertheless, competitiveness decreases in all three countries when moving from primary to processed products in the chains, which implies that value-adding opportunities are limited. Based on their competitive status, there is a potential in certain agro-food chains for supply chain integration and co-operation. Strategic alliances are important instruments for competitiveness. They create flexibility in operations, enhance technology transfer and networking and exploit possible complementary and supplementary relations between industries and organisations.
All-optical production of a large Bose-Einstein condensate in a double compressible crossed dipole trap

We report on an all-optical production of a $^{87}\mathrm{Rb}$ Bose-Einstein condensate (BEC) of ${10}^{6}$ atoms. We construct a double compressible crossed dipole trap (DCDT) formed by a high-power multimode fiber laser (MCDT) and a single-mode fiber amplifier (SCDT), which are both operated at $1.06\phantom{\rule{0.28em}{0ex}}\ensuremath{\mu}\mathrm{m}$. A very cold dense gas is first cooled by polarization gradient cooling in a three-dimensional optical lattice. More than $2\ifmmode\times\else\texttimes\fi{}{10}^{7}$ atoms are loaded into the enlarged DCDT. Both CDTs are then simultaneously compressed to significantly different sizes followed by evaporation, which is performed by lowering only the MCDT power. The tighter SCDT produces an extremely high collision rate and maintains the trap stiffness, which leads to rapid and efficient evaporation. After 0.4 s, a gas of $5\ifmmode\times\else\texttimes\fi{}{10}^{6}$ atoms with a phase-space density of 0.2 is confined within the SCDT alone. Further evaporation in 2.8 s yields a nearly pure BEC of $1.2\ifmmode\times\else\texttimes\fi{}{10}^{6}$ atoms in the $|F{m}_{F}\ensuremath{\rangle}=|11\ensuremath{\rangle}$ state. This number is the largest generated among all-optical methods. Our approach significantly improves the atom number of a condensate and circumvents the severe atom loss previously reported for multimode fiber lasers.
N-Methyl-d-aspartate Receptor Mechanosensitivity Is Governed by C Terminus of NR2B Subunit*

Background: The NMDA receptor mediates stretch-induced calcium influx and resulting neuronal excitotoxicity. Results: Calcium influx through NMDA receptors following stretch is reduced in cultures expressing NR2B C-terminal mutations. Conclusion: Mechanosensitivity of NMDA receptors is dependent on the NR2B subunit and PKC activity at the NR2B C terminus. Significance: These data provide insight into NMDA receptor subtype-specific mechanisms that dictate response to neuronal stretch. N-Methyl-d-aspartate receptors (NMDARs), critical mediators of both physiologic and pathologic neurological signaling, have previously been shown to be sensitive to mechanical stretch through the loss of its native Mg2+ block. However, the regulation of this mechanosensitivity has yet to be further explored. Furthermore, as it has become apparent that NMDAR-mediated signaling is dependent on specific NMDAR subtypes, as governed by the identity of the NR2 subunit, a crucial unanswered question is the role of subunit composition in observed NMDAR mechanosensitivity. Here, we used a recombinant system to assess the mechanosensitivity of specific subtypes and demonstrate that the mechanosensitive property is uniquely governed by the NR2B subunit. NR1/NR2B NMDARs displayed significant stretch sensitivity, whereas NR1/NR2A NMDARs did not respond to stretch. Furthermore, NR2B mechanosensitivity was regulated by PKC activity, because PKC inhibition reduced stretch responses in transfected HEK 293 cells and primary cortical neurons. Finally, using NR2B point mutations, we identified a PKC phosphorylation site, Ser-1323 on NR2B, as a unique critical regulator of stretch sensitivity. These data suggest that the selective mechanosensitivity of NR2B can significantly impact neuronal response to traumatic brain injury and illustrate that the mechanical tone of the neuron can be dynamically regulated by PKC activity.
Modeling Consumers' Adoption Intentions of Remote Mobile Payments in the United Kingdom: Extending UTAUT with Innovativeness, Risk, and

Mobile payments (MPs) are predicted to be one of the future’s most successful mobile services but have achieved limited acceptance in developed countries to date. PCs are still the preferred technology for online shopping in the United Kingdom but the continued growth of mobile commerce is highly correlated with the success of remote mobile payments (RMPs). Currently MP research has largely ignored the variations between different MP solutions, and existing MP adoption studies have predominantly utilized Davis’ (1989) Technology Acceptance Model, which has been criticized for having a deterministic approach without much consideration for users’ individual characteristics. Therefore, this study applied the Unified Theory of Acceptance and Use of Technology (UTAUT), extended with more consumer-related constructs, to explore the factors affecting non-users’ intentions to adopt RMP in the UK. Quantitative data was collected (n=268) and structural equation modeling was undertaken. The findings revealed that performance expectancy, social influence, innovativeness, and perceived risk significantly influenced non-users’ intentions to adopt RMP, whereas effort expectancy did not. Inclusion of MP knowledge as a moderating variable revealed that there was a significant difference in the effect of trust on behavioral intention for those who knew about MP than for those who did not. These findings have important theoretical and practical implications, particularly for the development and marketing of RMP which will support the long-term success of mobile commerce.
O crash de 2002: da “exuberância irracional” à “ganância infecciosa”

This paper is an attempt to discuss the macroeconomic repercussions from deinflating a speculative bubble in stock markets and from an established low price trend. Revelations accrued this low price trend how comprise recommendations by financial analysts, corporation balance sheets, auditing companies and credit rating agencies make the asset pricing difficult, affect confidence by financial agents and contaminate their expectations. The crisis of confidence brought about by these revelations can potentially impact on economic growth of developed countries, beginning with the USA, raise risk aversion by investors and trigger reinforced regulation and supervision mechanisms in detriment to auto-regulating ones which had been prevailing up to the present moment. JEL Classification: F65; G14; G23.
Regio‐ and Stereospecific Prenylation of Flavonoids by Sophora flavescens Prenyltransferase

Prenylflavonoids are valuable natural products that are widely distributed in plants. They often possess divergent biological properties, including phytoestrogenic, anti-bacterial, anti-tumor, and anti-diabetic activities. The reaction catalyzed by prenyltransferases represents a Friedel–Crafts alkylation of the flavonoid skeleton in the biosynthesis of natural prenylflavonoids and often contributes to the structural diversity and biological activity of these compounds. However, only a few plant flavonoid prenyltransferases have been identified thus far, and these prenyltransferases exhibit strict substrate specificity and low catalytic efficiency. In this article, a flavonoid prenyltransferase from Sophora flavescens, SfFPT, has been identified that displays high catalytic efficiency with high regiospecificity acting on C-8 of structurally different types of flavonoid (i.e., flavanone, flavone, flavanonol, and dihydrochalcone, etc.). Furthermore, SfPFT exhibits strict stereospecificity for levorotatory flavanones to produce (2S)-prenylflavanones. This study is the first to demonstrate the substrate promiscuity and stereospecificity of a plant flavonoid prenyltransferase in vitro. Given its substrate promiscuity and high catalytic efficiency, SfFPT can be used as an environmentally friendly and efficient biological catalyst for the regio- and stereospecific prenylation of flavonoids to produce bioactive compounds for potential therapeutic applications.