Miracle-dz/UniFAR-FTUs huggingface dataset:
Demonstration of a Scaling Advantage for a Quantum Annealer over Simulated Annealing

The observation of an unequivocal quantum speedup remains an elusive objective for quantum computing. The D-Wave quantum annealing processors have been at the forefront of experimental attempts to address this goal, given their relatively large numbers of qubits and programmability. A complete determination of the optimal time-to-solution (TTS) using these processors has not been possible to date, preventing definitive conclusions about the presence of a scaling advantage. The main technical obstacle has been the inability to verify an optimal annealing time within the available range. Here we overcome this obstacle and present a class of problem instances for which we observe an optimal annealing time using a D-Wave 2000Q processor over a range spanning up to more than $2000$ qubits. This allows us to perform an optimal TTS benchmarking analysis and perform a comparison to several classical algorithms, including simulated annealing, spin-vector Monte Carlo, and discrete-time simulated quantum annealing. We establish the first example of a scaling advantage for an experimental quantum annealer over classical simulated annealing: we find that the D-Wave device exhibits certifiably better scaling than simulated annealing, with $95\%$ confidence, over the range of problem sizes that we can test. However, we do not find evidence for a quantum speedup: simulated quantum annealing exhibits the best scaling by a significant margin. Our construction of instance classes with verifiably optimal annealing times opens up the possibility of generating many new such classes, paving the way for further definitive assessments of scaling advantages using current and future quantum annealing devices.
Dust composition and mass-loss return from the luminous blue variable R71 in the LMC

We present an analysis of mid-and far-infrared (IR) spectrum and spectral energy distribution (SED) of the LBV R71 in the LMC.This work aims to understand the overall contribution of high-mass LBVs to the total dust-mass budget of the interstellar medium (ISM) of the LMC and compare this with the contribution from low-mass asymptotic giant branch (AGB) stars. As a case study, we analyze the SED of R71. We compiled all the available photometric and spectroscopic observational fluxes from various telescopes for a wide wavelength range (0.36 -- 250\,$\mu$m). We determined the dust composition from the spectroscopic data, and derived the ejected dust mass, dust mass-loss rate, and other dust shell properties by modeling the SED of R71. We noted nine spectral features in the dust shell of R71 by analyzing Spitzer spectroscopic data. Among these, we identified three new crystalline silicate features. We computed our model spectrum by using 3D radiative transfer code MCMax. Our model calculation shows that dust is dominated by amorphous silicates, with some crystalline silicates, metallic iron, and a very tiny amount of polycyclic aromatic hydrocarbon (PAH) molecules. The presence of both silicates and PAHs indicates that the dust has a mixed chemistry. We derived a dust mass of 0.01 M$_\odot$, from which we arrive at a total ejected mass of $\approx$ 5 M$_\odot$. This implies a time-averaged dust mass-loss rate of 2.5$\times$10$^{-6}$ M$_\odot$\,yr$^{-1}$ with an explosion about 4000 years ago. We assume that the other five confirmed dusty LBVs in the LMC loose mass at a similar rate, and estimate the total contribution to the mass budget of the LMC to be $\approx$ 10$^{-5}$ M$_\odot$\,yr$^{-1}$, which is comparable to the contribution by all the AGB stars in the LMC. Based on our analysis on R71, we speculate that LBVs as a class may be an important dust source in the ISM of the LMC.
Embedded eye tracker in a real aircraft: new perspectives on pilot/aircraft interaction monitoring

Currently, online assessment of the aircrew performance focuses on behavioural data (flight data and pilot’s actions) and the detection may intervene too late for coping with the situation degradation. An early assessment of the pilot’s "internal state", based on physiological data collected from his autonomous nervous system (ANS) and predictive of his behaviour, is necessary. These data give clues both on the cognitive activity and on the emotional states and stress. The integration of ANS devices in a cockpit presents practical drawbacks and their use is often limited to simulators. In this preliminay study, the pros and cons of the adaptation of a standalone eye tracker in a light aircraft are presented. In spite of a sensitivity to light conditions and a definition of areas of interest limited to a part of the cockpit, the eye tracker has provided interesting behavioural (fixations) and physiological (pupillometry) measures in nominal (from take-off to landing) and degraded (provoke a simulated engine failure and plane down toward the airfield) conditions. The pilots spent less time glancing at the instruments, and focused on less instruments in the degraded condition. Moreover, the pupil size varied with the flight phases in the degraded condition, which reflected the variations of stress and attention levels. These encouraging results open two tracks: the development of new eye trackers able to overcome current technical limitations, and neuroergonomics researches providing guidelines for new man-machine interfaces integrating both flight and crew state vectors.
Examination of Job Satisfaction of the Medical Vocational High School Teachers.

The aim of this study is to determine the job satisfaction level of Medical Vocational High School teachers and whether it differs according to different variables. The research was organized in accordance with the screening model. The population of the research was composed of vocational course teachers who worked in Medical Vocational High Schools providing training in Istanbul in the 2013-2014 academic year. Sample was composed of 144 vocational course teachers chosen from 12 schools which were determined by the simple random cluster sampling method from within the general population. Personal Information Form developed by the researcher was used to determine the demographic characteristics of the group. Hackman and Oldham Job Satisfaction Scale, which was developed by Hackman and Oldham (1980) and which was adapted to Turkish by Silah (2002), was used to determine the job satisfaction level of the vocational course teachers at Medical Vocational High School. Job satisfactions of teachers constituting the sample group were observed to be medium-level. This also showed that the job satisfactions of medical vocational course teachers were at instability level. Teachers did not experience the feeling of high or low job satisfaction; they experienced the feeling of a medium level of job satisfaction. No statistically significant difference was observed among the arithmetic averages of the groups by the type of school they worked, gender, age, marital status, seniority and the residence status of teachers' job satisfaction.
Measurement of the atmospheric νe spectrum with IceCube

We present a measurement of the atmospheric nu(e) spectrum at energies between 0.1 and 100 TeV using data from the first year of the complete IceCube detector. Atmospheric nu(e) originate mainly from the decays of kaons produced in cosmic-ray air showers. This analysis selects 1078 fully contained events in 332 days of live time, and then identifies those consistent with particle showers. A likelihood analysis with improved event selection extends our previous measurement of the conventional v(e) fluxes to higher energies. The data constrain the conventional nu(e) flux to be 1.3(-0.3)(+0.4) times a baseline prediction from a Honda's calculation, including the knee of the cosmic-ray spectrum. A fit to the kaon contribution (xi) to the neutrino flux finds a kaon component that is xi = 1.3(-0.4)(+0.5) times the baseline value. The fitted/measured prompt neutrino flux from charmed hadron decays strongly depends on the assumed astrophysical flux and shape. If the astrophysical component follows a power law, the result for the prompt flux is 0.0(-0.0)(+3.0) times a calculated flux based on the work by Enberg, Reno, and Sarcevic.
Artificial ripening on banana (Musa Spp.) samples: Analyzing ripening agents and change in nutritional parameters

Abstract In recent years, the use of artificial fruit ripening agents has become prevalent mostly due to the commercial purposes. Different ripening agents are reported to be used to initiate the ripening process in fruits during off-seasons. However, the effects of these agents on the nutritional values of fruits are yet to be fully understood. The purpose of this study is to measure, analyze and compare the nutritional value of naturally and artificially ripened fruits. Bari-1 hybrid banana (Musa Spp.; local name: Sagor Kola) was chosen to carry out the experimental study. Ripe samples were collected directly from orchards or local markets. Additionally, unripe green samples were collected and artificially ripened in the laboratory using artificial ripening agents: ethephon, calcium carbide, ethylene glycol and fume from the kerosene stove. Different nutrition parameters, such as moisture content, total titratable acidity, vitamin C and sugar content were assessed for these banana samples. The assessed parameters of naturally and artificially ripened fruits were compared and analyzed to identify the change in nutritional values and determine the health hazards associated with them. The chemical compositions of artificial ripening agents were also investigated and possible health risks related to the impurities of ripening agents were assessed. Therefore, the key objective of this study is to address the changes in nutritional values and health risks associated with the artificial ripening which will be helpful for the consumers, nutritionists, physicians and other shareholders.
A quantitative/qualitative study on metaphors used by Persian depressed patients

Summary Aim. This study was designed to examine qualitatively/quantitatively the metaphors used by Iranian depressed patients. Metaphors, used by depressed patients, seem to be associated with personal failings or inadequacies. They may also contribute to the basis to account for a cultural notion of “depression”. Methods/materials . Filling in two metaphor inventories (Stem-Sentence Test: SST and Metaphor InventoFilling in two metaphor inventories (Stem-Sentence Test: SST and Metaphor Inventory: MI) and one clinical scale (Beck Depression Inventory: BDI), 30 healthy volunteers and 30 depressed patients matched for age and gender took part in this study. �uantitative/qualitative data analysis sho�uantitative/qualitative data analysis showed that depressed patients tended to produce metaphors with more negative emotional tone than healthy participants. results. Using the descriptive phenomenological analysis, the results indicated that participants likened depression using metaphors connoting darkness, being unable to escape/being lost, devastation and disease. Furthermore, depressed patients produced metaphoric phrases that are somehow pertinent to night time, lower positions, closed places, and hollow objects. In contrast, healthy participants tended to propose phrases related to day time, upper positions, open places, movement, and solid objects. Discussion. The present finding is in line with a phenomenon called mood congruent memory would be further supported by the construct accessibility model. Conclusion . The present findings are both similar and different from previous findings. These similarities and differences will be discussed from theoretical, clinical and cultural viewpoints. metaphor / depression / mood / memory / cultural differences
(Semi-)Analytic Gaussian Mixture Filter

Abstract In nonlinear filtering, special types of Gaussian mixture filters are a straightforward extension of Gaussian filters, where linearizing the system model is performed individually for each Gaussian component. In this paper, two novel types of linearization are combined with Gaussian mixture filters. The first linearization is called analytic stochastic linearization, where the linearization is performed analytically and exactly, i.e., without Taylor-series expansion or approximate sample-based density representation. In cases where a full analytical linearization is not possible, the second approach decomposes the nonlinear system into a set of nonlinear subsystems that are conditionally integrable in closed form. These approaches are more accurate than fully applying classical linearization.
Nonnegative matrix factorization for hyperspectral unmixing using prior knowledge of spectral signatures

Hyperspectral unmixing is a process aiming at identifying the constituent materials and estimating the corresponding fractions from hyperspectral imagery of a scene. Nonnegative matrix factorization (NMF), an effective linear spectral mixture model, has been applied in hyperspectral unmixing during recent years. As the data of hyperspectral imagery analyzed deeper, prior knowledge of some signatures in the scene could be available. In several scenes such as mining areas, a few surface substances like copper and iron are easy to identify through field investigation. Thus, their spectral signatures can be used as prior knowledge to unmix hyperspectral data. In such a context, we propose an NMF based framework for hyperspectral unmixing using such prior knowledge, referred to as NMFupk. Specifically, our algorithm supposes that some spectral signatures in the scene are known and then utilizes the prior knowledge of the spectral signatures to unmix the hyperspectral data. In a series of experiments, we test NMFupk and NMF without prior knowledge on both synthetic and real data. Results achieved demonstrate the efficacy of the proposed algorithm.
Inflammation and new bone formation: The long lasting debate in axial spondyloarthritis

In view of the argue on the 2 main hypotheses explaining a certain dissociation between inflammation and new bone formation [1], a multistep process has been claimed [8] assuming that all the pathogenetic mechanisms in the development of SpA run on parallel or gently intersecting tracks. The other assumption based on the previous study of Sieper et al. [9] would keep the door open for proving the suggested relation of inflammation and ongoing bone formation.
Transparency in Deep Reinforcement Learning Networks

In the recent years there has been a growing interest in the field of explainability for machine learning models in general and deep learning in particular. This is because, deep learning based approaches have made tremendous progress in the field of computer vision, reinforcement learning, language related domains and are being increasingly used in application areas such as medicine and finance. But before we fully adopt these models, it is important for us to understand the motivations behind network decisions. This helps us to gain trust in the network, to verify that network decisions are fair to those affected by it and to debug the network model. Moreover, it helps us to gain insights about underlying mechanisms learned by the network and understand the limitations of the network i.e. the domain in which the network performs well and conditions when the network fails. In this particular work, we explore transparency in deep reinforcement learning networks. We focus on answering the questionwhy a particular decision was taken by a value based deep reinforcement learning agent and identify attributes in the input space that positively or negatively influence its future actions in a human interpretable manner. Particularly, we discuss an approach “object saliency” at length and demonstrate that it can be used as a simple and effective computational tool for this purpose. We compare and contrast it with existing saliency approaches using a quantitative measure, discuss results from a pilot human experiment to study intuitiveness of object saliency and show how object saliency can provide insights into differences in value function learned by different RL architectures or training approaches, that is not highlighted by existing methods. We also show that it is possible to develop rule based textual descriptions of object saliency maps for easy interpretability by humans which is difficult to do with existing approaches.
Brazilian medical oncologists: current and future perspectives for 2020

Objective: In the USA there will be a shortage of medical oncologists by 2020. In Europe, a recent study showed that almost all analyzed countries will reach the estimated need. However, no data on this subject is available for Brazil, a developing country with a high cancer incidence. The aim of this study was to predict the Brazilian scenario for 2020. The number of practicing medical oncologists was obtained through Federal Council of Medicine in August 2014. Methods: Data on cancer incidence (excluding non-melanoma skin cancer) since 2008 were obtained from Brazilian National Cancer Institute (INCA). Results: Cancer incidence estimates for year 2020 were analyzed assuming a stable increase between 2014 and the subsequent years. Ratios of new cancer cases versus number of medical oncologists were calculated for 2014 and for 2020 per each Brazilian region. Based on the variation ratio per year, the Brazilian cancer incidence in 2020 is estimated to be 393,75/100,000 compared with 289,44/100,000 in 2014. The number of medical oncologists in Brazil will increase by 2020 in comparison to 2014, especially due to the growth of training vacancies. There will still be a heterogeneous distribution of medical oncologists through the different Brazilian regions and also a high number of patients per MO. Conclusion: The more critic region to oncology care seems to be the Midwest. This survey shows the need of a monitoring and planning program in oncology assistance in all Brazilian regions.
Using the critical incident technique to research decision making regarding access to training and development in medium-sized enterprises

Abstract Employees in small and medium-sized enterprises (SMEs) form part of a ‘disadvantaged’ group within the workforce that receives less access to training and development (T&D) than employees in large firms. Prior research into reasons for the relatively low levels of employee participation in training and development has typically involved surveys of owner/manager opinions. A novel and potentially more fruitful line of inquiry is investigating decisions managers have actually made regarding employee access to T&D. Building on this idea, we describe how the critical incident technique (CIT) was applied in our exploratory study of managerial decision making regarding employee access to training and development in medium-sized enterprises. We also discuss lessons learned in conducting the study. These lessons are based on an analysis of our experiences of using the CIT and are potentially important for researchers who will be using the technique to study similar topics in the years ahead.
On the Limitations of Using Situational Judgment Tests to Measure Interpersonal Skills: The Moderating Influence of Employee Anger

Many authors have suggested that situational judgment tests (SJTs) are useful tools for assessing applicants because SJT items can be written to assess a number of job-related knowledges, skills, abilities and other characteristics (KSAOs). However, SJTs may not be appropriate for measuring certain KSAOs for some applicants. We posit that using SJTs to measure interpersonal skills may lead to invalid inferences about applicants with higher levels of angry hostility (AH), and thus, AH should moderate the relation between interpersonally oriented SJTs and job performance. Three studies, using samples of healthcare workers (n = 225), police officers (n = 54), and medical doctors (n = 92), provided support for hypotheses in that that relations between SJT scores and performance criteria were significantly weaker among employees higher in AH compared to those lower in AH. In addition, none of the other facets of neuroticism tested (self-consciousness, anxiety, depression, immoderation, or vulnerability to stress) consistently moderated SJT validity, providing support for the uniqueness of AH. Implications for practice, and for future research studying the relations between interpersonal skills as measured by SJTs and job performance, are discussed.
Daily precipitation records over mainland Spain and the Balearic Islands

Abstract. Understanding the spatial distribution of extreme precipitations is of major interest in order to improve our knowledge of the climate of a region and its relationship with society. These analyses inevitably require the use of directly observed values to account for the actual extreme amounts rather than analyzed gridded values. A study of daily rainfall extremes observed over mainland Spain and the Balearic Islands is performed by using records from 8135 rain gauge stations from the Spanish Weather Agency (AEMET). Results show that the heaviest daily precipitations have been observed mainly on the coastal Mediterranean zone from Gibraltar to the Pyrenees. In particular, a record value of 817 mm was recorded in the Valencia region in 1987. The current map of daily records in Spain, which updates the pioneering work of the Spanish meteorologist Font, shows similar distribution of extreme events but with notably higher amounts. Generalized extreme values distributions fit the Mediterranean and Atlantic rain gauge measurements and shows the different characteristics of the extreme daily precipitations in both regions. We identify the most extreme events (above 500 mm per day) and provide a brief description of a typical meteorological situation in which these damaging events occur. An analysis of the low-level circulation patterns producing such extremes – by means of simple indices such as NAO, WeMOi and IBEI – confirms the relevance of local flows in the generation of either Mediterranean or Atlantic episodes. WeMOi, and even more IBEI, are good discriminants of the region affected by the record precipitation event.
Determinants of transfer of training: A comprehensive literature review

Investments in training measures can only be considered effective if the transfer of the learned contents to practical situations is continuously successful. In this context the scientific and professional discourse regarding the effectiveness of further education, especially regarding training transfer, has intensified considerably. This analysis provides a systematic and comprehensive overview of the current state of international empirical research regarding major influencing factors of learning transfer in the context of formalized further vocational training. Our review of literature differentiates the most important influencing factors on the micro-level of the specific individual characteristics of the participants, the meso-level of measure-specific characteristics of the field of learning, as well as institutional characteristics of the work environment at the macro-level. Decades of transfer research brings forth a wealth of information regarding factors which influence the learning transfer. The current analysis systematizes these results and clarifies that the current state of research regarding the determinants of the process of learning transfer shows clear trends. But there are also some inconsistent findings. Thus the question of which factors positively influence the success of learning transfer is well-studied for the micro-level in particular. The article shows that there is still a research deficit concerning the major determinants of learning transfer at the meso- and macro-level. Finally, in this context this article identifies promising directions for future research.