Miracle-dz/UniFAR-FTUs huggingface dataset:
DETECTING OF INHOMOGENEITIES IN TIME SERIES USING REAL PRECISION METHOD

Rainfall data analysis under Global Change scenarios in Mediterranean landscapes are under specifically constrains, given the paucity, torrentially, seasonality and irregularity of rainfall regime in these areas. So the approach to rainfall analysis is needed of a very dense data base to control the spatial diversity of rainfall regime. From 2000, we are trying to construct, by using complete original data base stored at National Meteorological Institutions (INM), a monthly precipitation data base as dense as possible for Spanish Mediterranean climate area. The original INM source is composed by a big amount of data (near 4000 rainfall series for an area of 150.000 km) but presents many quality problems. There exist more than 300 series older than 1930, but no one of them continuous recording data today. Moreover, gaps higher than 20 years are frequent. In contrast, redundancy and overlapping are common and usually more than one observatory in the same location is available. Thus, reconstruction process is the first steep in order to obtain a dense, complete and homogeneous data base for this area. For these purpose, we have adopted a general procedure for reconstruction, using Geographical Information System, at two spatial levels: the local level, i.e. rainfall observatories in the same place or far away under specific threshold (less than 5 km) and the subregional level using reference stations. The quality control of reconstructed series is checked by common homogeneization procedures (i.e. SNHT and others) following the general scheme proposed by Štepánek (2003), and considering the meta-data information produced by reconstruction processes itself. The homogeneization analysis is carried out by AnClim software available at Internet. The initial results produce a very dense data base (overall mean 1 station per 200 km) in the Valencia Region and in the central Ebro Basin (the coastland east and north east inland area). The percentage of observed inhomogeneities let us to indicate that reconstruction process used do not produce a noticeable amount of inhomogeneities in the final series. The global data base is at present under construction, so we present some results of the analysis of such a previous subregional data base for 1951-2000.
Reinforcement Learning with Dynamic Movement Primitives-DMPs

In this project we set up the AMARSi Oncilla Simulator and used Dynamic movement primitivies (DMPs) as movement representation and optimized their parameters in a reinforcement learning framework to adapt the robot’s behaviour to new problems. After some experiments on toy examples we applied an open-loop control scheme to the Oncilla Simulator. In the end we want to apply this approach to a real robot, the AMARSi Oncilla quadroped and evaluate its performance.
Early Detection of Cancer using Soft Computing

Cancer is one of the most frequent cause of death for both men and women. The early detection of cancer is very essential to provide the timely treatment so that the probability of curing the disease increases. The pain and toxicity can be minimized if the disease is found in initial stages. Medical image mining refers to the application in data mining techniques on medical image data. The main goal of medical image mining is to extract clinically relevant information from the medical images to assist the physicians in accurate diagnosis and detection of diseases. Soft computing is a consortium of methodologies that provides flexible information processing capability. Soft computing techniques such as fuzzy sets, neural networks, genetic algorithms, and rough sets are most widely applied for Cancer image mining. This paper presents the early detection of Cancer based on image mining using soft computing techniques. Hence the related issues can be resolved suitably using most efficient soft computing based image mining techniques.
TRANSVERSE FEEDBACK SYSTEM FOR THE CERN FCC-hh COLLIDER

For the future hadron Collider (FCC-hh) being studied at CERN a strong transverse feedback system is required to damp coupled bunch instabilities. This system is also planned to be used for injection damping. Based on the LHC transverse feedback design, we derive requirements for power and kick strength for this system and consider different options of bunch spacing, 25 ns and 5 ns, and injection energy. Operation at high gain and close to a half integer tune is being considered and constrains the layout and signal processing. Requirements for the pick-up resolution are high in order to keep the emittance increase small. The performance is evaluated using numerical simulations based on the headtail code. Future areas of research and development and possible prototype developments are outlined.
Vocally disruptive behavior in the elderly 655 Table 1 . Typology of VDB

Background: Vocally disruptive behavior (VDB) in the elderly is a common condition, especially in people with dementia, but difficult to treat. It may occur in as many as 40% of nursing home residents. This study is a review of the existing literature on this condition. Method: The literature review was conducted using PubMed (particularly Medline and the Cochrane database) and reference lists from relevant publications in English, French, and German. Results: Most studies are small and no conclusive prevalence data are available. Many biological and psychosocial treatments have been advocated, but most studies are little more than anecdotal case reports. It is evident that VDB can have deleterious consequences on others and the patients themselves, although no studies specifically examine the range or the pervasiveness of VDB. Etiopathogenic research on VDB is still in its infancy. Conclusions: Most aspects surrounding VDB are insufficiently understood. The heterogeneity and multiple contributive factors regarding VDB suggest quite convincingly that a panoply of different interventions tailored to the individual’s needs will be required to overcome VDB and the suffering related to it.
Title : Goal setting for weight-related behavior change in children : an exploratory study

Aim: The primary aim was to explore how proficient parents are in setting health behaviour goals for their children according to SMART goal principles. A secondary aim was to examine associations between goalsetting and change in health behaviors. Methods: Participants were parents and children taking part in one of two trials incorporating goal-setting. Study 1 (Time2bHealthy) was an online program for parents of preschoolers (n=36) and Study 2 (HIKCUPS) was a three-arm face-to-face trial examining a parent-centered dietary intervention (Study2Diet), a childcentered physical activity intervention (Study2PA), or combination of both (Study2Combo) (n=83). Goals were coded on five ‘SMART’ principles. Goals were scored 1 or 0 for each principle (1 indicated the principle was met and 0 not met). The total maximum score for each goal was 5. Mean total goal-score and means for each SMART principle were calculated. Results: Mean (SD) goal-setting scores for Study 1 were 3.84 (0.61), Study2Diet 2.17 (1.33), Study2PA 3.18 (1.45) and Study2Combo 2.24 (1.30). Goal-scores were significantly higher for Study 1 than Study 2 (p<0.001). In Study2Diet, goal-setting was significantly associated with greater reduction in energy intake (p=0.019). Conclusions: Goal-scores were highest in Study 1, which used a supported online format for setting goals. Parents were better at setting physical activity goals, but these goals did not translate into improvements in physical activity behavior. Goals set by parents may be useful in energy intake reduction, however further research is required to determine benefits for weight status or physical activity.
REM DESIGN FOR COGNITIVE RADIO NETWORKS IN TV BAND

Recent studies have demonstrated a clearly visible fact in our environment: The boom of wireless networks traffic has made raise the need of more bandwidth, due to an increment of the usage of wireless resources; every time with more and more different devices. Otherwise, other studies show an inefficient occupation of radio electric spectrum inside commercial bands; that is, not all assigned channels are currently in use by their operators. UHF TV band is an example of this situation, compounded after analogue TV switching off. Putting two previous scopes together have induced a new evolution of wireless networks: Deploying a certain kind of devices able to operate at empty channels of commercial bands. This thesis shows a way for these wireless devices to find out empty channels of a certain band and geographical location. The way has been tried out at ETSETB TelecomBCN UPC Campus Nord facilities with successful expected results.
Analytical Methods for Determination of Sitagliptin : An Updated

Sitagliptin is an oral anti-hyperglycemic agent of the dipeptidyl peptidase-4 (DPP-4) inhibitor class used in the treatment of type-2 diabetes. It stimulates insulin release and reduces glucagon level by inhibition of inactivation of the incretin in a glucose-dependant manner. In 2013 it was the second best-selling drug in the U.S. This review explores the reported analytical methods so far in the literature for the estimation of sitagliptin in bulk drug, pharmaceutical formulations and in biological matrix. This assessment encompasses various analytical methods such as spectrometry, high performance liquid chromatography (HPLC), liquid chromatography-electrospray ionization-mass spectrometry (LC-ESI-MS-MS), liquid chromatography-mass spectrometry (LC-MS), capillary electrophoresis (CE), ultra performance liquid chromatography (UPLC), high performance thin layer chromatography (HPTLC) and gas chromatography-mass spectrometry (GC-MS) for the estimation of sitagliptin in single and/or in combination.
Systemic Shocks , Banking Spreads and the External Finance Premium Draft Copy-Not for Circulation or Citation

In this paper, we study the dynamics of the external nance premium in an accelerator model of the economy. To better capture the dynamics in nancial crises, we use features of a regulated banking sector as well as a notion of systemic risk. The model produces an external nance premium that is an increasing function of systemic risk. As well, it nds that bank leverage is also positively related to increased spreads, but only when the economy is in stress. That is, changes in bank regulatory requirements have little impact in good times, but act as a multiplier when the economy is an a badstate. JEL Classi cation : E52, E58, G18, G28
Assessment of nutritional status and body image perceptions on immigrants

The valuation of the nutritional status and body image perception of the immigrant population is important to detect exposed groups at risk and to make nutritional recommendations. The assessment of nutritional status can be carried out through different methods, among which Anthropometric ones are especially recommended in case of large immigrant flow. This assessment is an important basis for developing an effective strategy to improve nutrition and health status in immigrants. Abstract La valutazione dello stato nutrizionale e della percezione della immagine corporea nella popolazione d’immigrati e importante per l’individuazione di gruppi a rischio, in modo da fornire le opportune raccomandazioni nutrizionali. La valutazione dello stato nutrizionale puo essere effettuata mediante diverse metodologie. Il ricorso ai metodi antropometrici e particolarmente consigliabile nel caso di un grande flusso d’immigrati. Questa valutazione puo costituire un’importante base di partenza per sviluppare una strategia utile a migliorare lo stato nutrizionale e di salute dell’immigrato. La valutazione dello stato nutrizionale e della percezione della immagine corporea nella popolazione d’immigrati e importante per l’individuazione di gruppi a rischio, in modo da fornire le opportune raccomandazioni nutrizionali. La valutazione dello stato nutrizionale puo essere effettuata mediante diverse metodologie. Il ricorso ai metodi antropometrici e particolarmente consigliabile nel caso di un grande flusso d’immigrati. Questa valutazione puo costituire un’importante base di partenza per sviluppare una strategia utile a migliorare lo stato nutrizionale e di salute dell’immigrato. 1-Introduction on nutritional status The nutritional status is the current condition of health of a person or a group related to their intake and utilization of nutrients. It is influenced by endogenous (age, gender, ethnicity) and exogenous (nutrition behavior, physical activity, cultural, social and economic circumstances, etc.) factors. Malnutrition is the consequence of a lack or excess of nutrients and/or faulty utilization of them. Currently malnutrition, leading to either underweight or overweight, is one of the major public health problem (Livingstone, 2001; Kaur et al, 2003; United Nations Children’s Fund et al, 2012; Olearo et al, 2014; etc.).
Performance Appraisals Impact on Attitudinal Outcomes and Organizational Performance

Performance appraisal is a widely recognized process, yet in Iran efforts to study and examine its effect on attitudinal outcomes and firm performance are scarce. The present study addresses this research gap. Researchers explored the relationship between PA satisfaction, job satisfaction and turnover intentions in semi-governmental organizations in Iran. Using responses collected from 123 respondents, we find statistically significant relationships between studied variables. The results have significant policy implications for improving the process of performance appraisal in semi-governmental organizations in Iran as well as other developing countries. Further the study enriches the body of knowledge on performance appraisal and its impact on organizational performance in developing countries.
SPS 2018 , 16-18 May 2018 , Stockholm , Sweden A life cycle approach to business performance measurement systems

Under the concept of "Industry 4.0", production processes will be pushed to be increasingly interconnected, information based on a real time basis and, necessarily, much more efficient. In this context, capacity optimization goes beyond the traditional aim of capacity maximization, contributing also for organization’s profitability and value. Indeed, lean management and continuous improvement approaches suggest capacity optimization instead of maximization. The study of capacity optimization and costing models is an important research topic that deserves contributions from both the practical and theoretical perspectives. This paper presents and discusses a mathematical model for capacity management based on different costing models (ABC and TDABC). A generic model has been developed and it was used to analyze idle capacity and to design strategies towards the maximization of organization’s value. The trade-off capacity maximization vs operational efficiency is highlighted and it is shown that capacity optimization might hide operational inefficiency. © 2017 The Authors. Published by Elsevier B.V. Peer-review under responsibility of the scientific committee of the Manufacturing Engineering Society International Conference 2017.
Application of Bayesian statistics to estimate nitrous oxide emission factors of three nitrogen fertilisers on UK grasslands

Trapezoidal integration by linear interpolation of data points is by far the most commonly used method of cumulative flux calculations of nitrous oxide (N2O) in studies that use flux chambers; however, this method is incapable of providing accurate uncertainty estimates. A Bayesian approach was used to calculate N2O emission factors (EFs) and their associated uncertainties from flux chamber measurements made after the application of nitrogen fertilisers, in the form of ammonium nitrate (AN), urea (Ur) and urea treated with Agrotain® urease inhibitor (UI) at four grassland sites in the UK. The comparison between the cumulative fluxes estimated using the Bayesian and linear interpolation methods were broadly similar (R= 0.79); however, the Bayesian method was capable of providing realistic uncertainties when a limited number of data points is available. The study reports mean EF values (and 95% confidence intervals) of 0.60 ± 0.63, 0.29 ± 0.22 and 0.26 ± 0.17% of applied N emitted as N2O for the AN, Ur and UI treatments, respectively. There was no significant difference between N2O emissions from the Ur and UI treatments. In the case of the automatic chamber data collected at one site in this study, the data did not fit the log-normal model, implying that more complex models may be needed, particularly for measurement data with high temporal resolution.
Adversarial autoencoder analysis on human μ ECoG dataset

Building scalable generative models to capture rich distributions in human μECoG dataset could potentially leads to discovering neural patterns and hence better understanding of how human brain function. In recent years, generative models have been developed that may be trained via direct back-propagation and avoid the difficulties that come with MCMC training, which used by Deep Belief Network and Deep Boltzman Machines. For example, variational autoencoder [1] use a encoder network to predict the posterior distribution over latent variables, generative adversarial network [2] use an adversarial training procedure to directly shape the output distribution. Adversarial autoencoder(AAE[3]) combines this two and turn an autoencoder into a generative model. In their approach, an autoencoder is trained with dual objectives – a traditional reconstruction error criterion, and an adversarial training criterion. The result of the training is that the encoder learns to convert the data distribution to the prior distribution, while the decoder learns a deep generative model that maps the imposed prior to the data distribution. Fig. 1 shows the general structure of AAE.
The impact of biochar doses on soil quality and microbial functional diversity

Changes of soil biological activity and microbial diversity were assessed after application of biochar in different doses. The biochar doses were determined based on the initial carbon content in the soil, and they were increased to 2.5%, 5%, 10%, 20%, 50%, and 100% in the experimental conditions. The experiment design also included a control condition, which was not treated with biochar. The basic biological activities in the soil, i.e., enzymatic activity and the content of carbon and nitrogen in the microbial biomass, were determined. Additionally, the functional biodiversity of soil microorganisms was assessed using the Biolog EcoPlates method. It was demonstrated that biochar added to the soil at the dose of 10 to 20% significantly increased soil biological activity and functional diversity. The biochar dose of 10 to 20% was the optimal dose for enhancement of soil biological activity. This dose induced a significant increase in the total carbon content in the microbial biomass, enzymatic activity, and the overall content of total and easily extractable glomalins. The highest values of the Shannon and AWCD indices were determined in soil supplemented with 5 to 20% of biochar.
CHAOS FOR EXAMINING THE FUNDAMENTAL PERIOD OF SOILS

In this paper an alternative vision, based on the Chaos Theory, for the analysis of soils systems oscillating under seismic forces is described. The topological tool, Recurrence Plots RPs, enables recognition and treatment of accelerations recorded in seismological stations located on soil deposits. The chaotic attributes obtained from RPs are interpreted for determining the natural period of vibration. This dynamic non-linear characterization could help in the evolution or reinterpretation of some partially understood aspects of seismic phenomena.
PR EP RI NT Declarative User Selection with Soft Constraints

In applications with large userbases such as crowdsourcing, social networks or recommender systems, selecting users is a common and challenging task. Different applications require different policies for selecting users, and implementing such policies is application-specific and laborious. To this end, we introduce a novel declarative framework that abstracts common components of the user selection problem, while allowing for domain-specific tuning. The framework is based on an ontology-based representation of user profiles, with respect to which we define a query language for policy specification. Our language extends SPARQL with means for capturing soft constraints which are essential for user selection. At the core of our query engine is then a novel efficient algorithm for handling these constraints. Our experimental study on real-life data indicates the effectiveness and flexibility of our approach, showing in particular that it outperforms existing task-specific solutions in prominent user selection tasks.
Changing Forms and Platforms of Misogyny: Sexual Harassment of Women Journalists on Twitter

Across time, in a variety of forms and spaces -from homes and workplaces to digital domains of social mediawomen have become victims of male dominance. So also are the other vulnerable sections that suffer multi-layered abuse, and endure sexual harassment in social media. Yet, this phenomenon is insufficiently explored. Therefore, this article argues that social media spaces have become domains for sexual harassment and subjugation of women. This article examines gender-trolling on Twitter as a form of sexual violence against women. Employing qualitative analyses of the Twitter conversations on Indian journalists, namely Barkha Dutt, Sagarika Ghose, and Rana Ayyub, it exposes the nature and form of sexual violence against women on the micro-blogging space, and argues that social media platforms constitute convenient havens of harassment against assertive women
Metadata of the chapter that will be visualized in SpringerLink

Automatic assessment of programming tasks in MOOCs (Massive Open Online Courses) is essential due to the large number of submissions. However, this often limits the scope of the assignments since task requirements must be strict for the solutions to be automatically gradable, reducing the opportunity for solutions to be creative. In order to alleviate this problem, we introduce a system capable of assessing the graphical output of a solution program using image recognition. This idea is applied to introductory computer graphics programming tasks whose solutions are programs that produce images of a given object on the screen. The image produced by the solution program is analysed using image recognition, resulting in a probability of a given object appearing in the image. The solution is accepted or rejected based on this score. The system was tested in a MOOC on 2,272 solution submissions. The results contained 4.6% cases of false negative and 0.5% cases of false positive grades. The method introduced in this paper saved approximately one minute per submission of the instructors’ time compared to manual grading. A participant survey revealed that the system was perceived to be functioning well or very well by 82.1% of the respondents, with an average rating of 4.4 out of 5.