Miracle-dz/UniFAR-FTUs huggingface dataset:
Análisis econométrico del enoturismo en España: un estudio de caso

Econometric Analysis of Wine Tourism in Spain. A Case Study. This paper presents a case study aiming to evaluate the economic potential of wine tourism in a certain area (Montilla-Moriles in Cordoba, Southern Spain). Aspects analyzed are offer and demand, evolution and perspectives of the wine route Montilla-Moriles and the visitor's consumer profile in order to find a correlation between what entrepreneurs offer and what clients demand.
Radiologic and Functional Evaluation of Electrode Dislocation from the Scala Tympani to the Scala Vestibuli in Patients with Cochlear Implants

BACKGROUND AND PURPOSE: Localization of the electrode after cochlear implantation seems to have an impact on auditory outcome, and conebeam CT has emerged as a reliable method for visualizing the electrode array position within the cochlea. The aim of this retrospective study was to evaluate the frequency and clinical impact of scalar dislocation of various electrodes and surgical approaches and to evaluate its influence on auditory outcome. MATERIALS AND METHODS: This retrospective single-center study analyzed a consecutive series of 63 cochlear implantations with various straight electrodes. The placement of the electrode array was evaluated by using multiplanar reconstructed conebeam CT images. For the auditory outcome, we compared the aided hearing thresholds and the charge units of maximum comfortable loudness level at weeks 6, 12, and 24 after implantation. RESULTS: In 7.9% of the cases, the electrode array showed scalar dislocation. In all cases, the electrode array penetrated the basal membrane within 45° of the electrode insertion. All 3 cases of cochleostomy were dislocated in the first 45° segment. No hearing differences were noted, but the charge units of maximum comfortable loudness level seemed to increase with time in patients with dislocations. CONCLUSIONS: The intracochlear dislocation rate of various straight electrodes detected by conebeam CT images is relatively low. Scalar dislocation may not negatively influence the hearing threshold but may require an increase of the necessary stimulus charge and should be reported by the radiologist.
The discrimination of visual number.

Suppose that there are two collections or groups of objects-coins, trees, beans, or aircraft-and we do not know how many objects there are. Suppose further that for some reason we cannot count the number of objects in either group. Still, some property of each group makes it possible for a person to say that one of these groups is greater-than, lessthan, or equal-to the other group. It is this property of a collection of objects that we define as numerousness.l We might say that numerousness is that property of a group of objects which we can discriminate, without counting, under instruction to judge how many objects the group contains. We shall wish to modify this definition later as a result of the experiments reported in this paper, but it is adequate for the present discussion of the problem. The judgment of 'numerousness' may be made in several different ways: (a) it may be comparative-more numerous or less numerous, larger or smaller, etc.; (b) or it may be 'absolute. ' There is one special form that the absolute judgment of numerousness can take. It is called the direct reporting of number. In this method of reporting, a numeral is assigned to represent how many things there are in any given collection of objects. After a brief look-so brief that counting is impossible-we say 10, 23, or 250 to indicate that we estimate that the group contained 10, 23, or 250 members.
Sea surface temperature variability in coastal areas of the northeastern Pacific related to the El Niño‐Southern Oscillation and the Pacific Decadal Oscillation

We examined monthly time‐series (1950 to 1999) of sea surface temperature (SST) anomalies in 47 quadrants (2° × 2°) along the coast of North America and their relation to the El Niño‐Southern Oscillation (ENSO) and the Pacific Decadal Oscillation (PDO). We used the Multivariate ENSO Index (MEI) and the PDO Index (PDOI) and assumed a linear interaction of the mechanisms behind their interannual variations. Then, we examined SST anomalies as functions of MEI and PDOI using multiple linear regression (MLR). On average, ENSO influence decreases poleward but is still dominant at 31°N. Northward, the PDO signal dominates. MLR was also applied to selected sea level height (SLH) series. ENSO effects on SLH were clear up to 48°N, while PDO showed a weak effect only in the Gulf of Alaska. This suggests that, poleward of Southern California, ENSO effects may be largely restricted to the inshore coastal environment.
A Multi-Timescale and Bilevel Coordination Approach for Matching Uncertain Wind Supply With EV Charging Demand

The matching between random wind supply and electric vehicle (EV) charging demand can reduce the requirement of traditional power sources and the emission of CO2. This problem is of great practical interest but involves system dynamics in multiple timescales. We consider this an important problem in this paper. In order to capture the randomness in the wind supply and EV charging demand, we formulate the problem as a bilevel Markov decision process. At the upper level, the charging demand of EVs in different locations is aggregated into multiple aggregators. The system operator dispatches power among the aggregators in a coarse timescale to maximize the wind power utilization. At the lower level, the aggregator schedules the charging process of individual EVs at a finer timescale to minimize the charging cost. In order to solve this large-scale problem, a bilevel simulation-based policy improvement (SBPI) method is developed. It is mathematically proved that the SBPI can improve from base policies in both levels. The performance of this multi-timescale and bilevel coordination approach is demonstrated through case studies in the city of Beijing.
Comparative Proteomics of Excretory-Secretory Proteins Released by the Liver Fluke Fasciola hepatica in Sheep Host Bile and during in Vitro Culture ex Host*S

Livestock infection by the parasitic fluke Fasciola hepatica causes major economic losses worldwide. The excretory-secretory (ES) products produced by F. hepatica are key players in understanding the host-parasite interaction and offer targets for chemo- and immunotherapy. For the first time, subproteomics has been used to compare ES products produced by adult F. hepatica in vivo, within ovine host bile, with classical ex host in vitro ES methods. Only cathepsin L proteases from F. hepatica were identified in our ovine host bile preparations. Several host proteins were also identified including albumin and enolase with host trypsin inhibitor complex identified as a potential biomarker for F. hepatica infection. Time course in vitro analysis confirmed cathepsin L proteases as the major constituents of the in vitro ES proteome. In addition, detoxification proteins (glutathione transferase and fatty acid-binding protein), actin, and the glycolytic enzymes enolase and glyceraldehyde-3-phosphate dehydrogenase were all identified in vitro. Western blotting of in vitro and in vivo ES proteins showed only cathepsin L proteases were recognized by serum pooled from F. hepatica-infected animals. Other liver fluke proteins released during in vitro culture may be released into the host bile environment via natural shedding of the adult fluke tegument. These proteins may not have been detected during our in vivo analysis because of an increased bile turnover rate and may not be recognized by pooled liver fluke infection sera as they are only produced in adults. This study highlights the difficulties identifying authentic ES proteins ex host, and further confirms the potential of the cathepsin L proteases as therapy candidates.
The Role of γ-Tubulin in Centrosomal Microtubule Organization

As part of a multi-subunit ring complex, γ-tubulin has been shown to promote microtubule nucleation both in vitro and in vivo, and the structural properties of the complex suggest that it also seals the minus ends of the polymers with a conical cap. Cells depleted of γ-tubulin, however, still display many microtubules that participate in mitotic spindle assembly, suggesting that γ-tubulin is not absolutely required for microtubule nucleation in vivo, and raising questions about the function of the minus end cap. Here, we assessed the role of γ-tubulin in centrosomal microtubule organisation using three-dimensional reconstructions of γ-tubulin-depleted C. elegans embryos. We found that microtubule minus-end capping and the PCM component SPD-5 are both essential for the proper placement of microtubules in the centrosome. Our results further suggest that γ-tubulin and SPD-5 limit microtubule polymerization within the centrosome core, and we propose a model for how abnormal microtubule organization at the centrosome could indirectly affect centriole structure and daughter centriole replication.
Gain-equalized, eight-wavelength WDM optical add-drop multiplexer with an 8-dB dynamic range

The performance of a gain-equalized, eight-wavelength WDM optical add-drop multiplexer (W-ADM) has been measured. By operating the EDFA 9-dB into saturation, the gain was equalized to within 1 dB with a minimum gain of 15 dB, over a 20-nm optical bandwidth and for total input signal power variations of 8 dB. The individual output powers were constant to within 1 dB over a 6-dB range of input powers. These results indicate that for a large range of input signal powers it would not be necessary to readjust the EDFA gain equalizer. However, pump power degradation had a stronger impact on gain variation: a 1.4-dB reduction of pump power caused gain variations of 1.8 dB. In addition, polarization-dependent losses of the W-ADM induced output power fluctuations of 1.6 dB. <<ETX>>
Design of Infrastructure Wireless Mesh Networks: Formulations and Solutions

The design/planning of WMNs is a key phase before any deployment. Few proposals can be found in the open literature that deals with the design problem; however, they do not take into account all the parameters that have an impact on the outcome of the design and they assume the existence of a physical topology where the location and the characteristics of nodes (e.g., number of channels, number of radios) are fixed.In this paper, we define a generalized model for the WMNs design problem that takes into account all the parameters that have a significant impact on the network (interference, multi-channel, transmission power, etc.), expected traffic, the constraints of the physical environment (potential locations of wireless routers and gateways), etc. To resolve the generalized model, we propose a combination of genetic and tabu search algorithms. The objective is to minimize the cost of the network and its operations while satisfying the requirements.
On Modeling and Measuring Inter-dependencies among Critical Infrastructures

During the last years man efforts have been devoted to inspect the inter-dependence among Critical Infrastructures. Even assuming that the asset owners are supposed to handle their own possible misbehaviours properly, critical events maybe triggered by infrastructure's interactions. Therefore the need to handle and possibly measure inter-dependencies. Within this perspective, the EU funded MIA Project which basic aim is to assess some measures to quantify inter-dependencies among Critical Infrastructures (energy and ICT networks) for the topological and the service level. We report recent outcomes of that project based on topological information and especially on spectral analysis that can be related to dynamical properties of the electric and telecommunication systems. A topological concepts of "Relevance" is applied for the first time to the real electric network of Roma area.
Building Trustworthy Systems: Lessons from the PTN and Internet

The public telephone network (PTN) and Internet are two large and complex networked information systems (NISs). The PTN and the Internet shed light on the technical problems faced by the developers and operators of other NISs. In some ways, the two networks are very similar. No single entity owns, manages, or can even have a complete picture of either. Both networks involve large numbers of subsystems operated by different organizations. The number and intricate nature of the interfaces that exist at the boundaries of these subsystems are one source of complexity; the increasing popularity of advanced services is a second source. This article discusses vulnerabilities in the PTN and Internet, identifying ways new research might help to eliminate those vulnerabilities.
The genetic control of cell proliferation in Drosophila imaginal discs

Summary The imaginal discs of Drosophila provide a favorable system for the analysis of the mechanisms controlling developmental cell proliferation, because of the separation in time between cell proliferation and differentiation, and the facility with which controlling genes can be identified and characterized. Imaginal discs are established in the embryo, and grow by cell proliferation throughout the larval period. Proliferation terminates in a regular spatial pattern during the final stages of larval development and the first day of pupal development. Cell proliferation can be locally reactivated in growth-terminated imaginal discs by removing part of the disc and culturing the remaining fragment in an adult host. The pattern of proliferation in these fragments suggests that cell proliferation in imaginal discs is controlled by direct interactions between cells and their neighbors. Proliferation appears to be stimulated by positional information differences, and these differences are reduced by the addition of new cells during tissue growth. Genes involved in cell proliferation control have been identified by collecting and analyzing recessive lethal mutations which cause overgrowth of imaginal discs. In some of these mutants (fat, lgd, c43, dco) the overgrowing tissue is hyperplastic; it retains its single-layered epithelial structure and is capable of differentiating. In two of the hyperplastic mutants (dco and c43), the imaginal discs show a failure of gap-junctional cell communication, suggesting that this form of cell communication may be involved in termination of proliferation. In other mutants the overgrowing disc tissue is neoplastic: it loses its structure and ability to differentiate, becoming a tumorous growth. The two genes that give a neoplastic phenotype (dlg and lgl) have been cloned and cDNAs of one of them (lgl) sequenced. The lgl gene encodes a cell surface molecule with significant homology to calcium-dependent cell adhesion molecules (cadherins). The expression of lgl at the time of termination of cell proliferation suggests that there are changes in the way that cells interact with one another at these times, and that these changes may be implemented by cell adhesion molecules. Direct cell contact within the epithelium, as well as signalling through gap junctions, appears to be involved in the cell interactions needed for the termination of cell proliferation. Mutations in genes encoding the Drosophila homologs of growth factors, growth factor receptors and oncogenes usually show an effect on cell-fate decisions rather than cell proliferation control, but this may be because oncogenic mutations in these genes would be dominant lethals and would therefore not be identified by conventional genetic analysis.
Representation Learning via Semi-Supervised Autoencoder for Multi-task Learning

Multi-task learning aims at learning multiple related but different tasks. In general, there are two ways for multi-task learning. One is to exploit the small set of labeled data from all tasks to learn a shared feature space for knowledge sharing. In this way, the focus is on the labeled training samples while the large amount of unlabeled data is not sufficiently considered. Another way has a focus on how to share model parameters among multiple tasks based on the original features space. Here, the question is whether it is possible to combine the advantages of both approaches and develop a method, which can simultaneously learn a shared subspace for multiple tasks and learn the prediction models in this subspace? To this end, in this paper, we propose a feature representation learning framework, which has the ability in combining the autoencoders, an effective way to learn good representation by using large amount of unlabeled data, and model parameter regularization methods into a unified model for multi-task learning. Specifically, all the tasks share the same encoding and decoding weights to find their latent feature representations, based on which a regularized multi-task softmax regression method is used to find a distinct prediction model for each task. Also, some commonalities are considered in the prediction models according to the relatedness of multiple tasks. There are several advantages of the proposed model: 1) it can make full use of large amount of unlabeled data from all the tasks to learn satisfying representations, 2) the learning of distinct prediction models can benefit from the success of autoencoder, 3) since we incorporate the labeled information into the softmax regression method, so the learning of feature representation is indeed in a semi-supervised manner. Therefore, our model is a semi-supervised autoencoder for multi-task learning (SAML for short). Finally, extensive experiments on three real-world data sets demonstrate the effectiveness of the proposed framework. Moreover, the feature representation obtained in this model can be used by other methods to obtain improved results.
DEVELOPMENT OF CHRONIC INJURY AND NATURE OF INTERSTITIAL INFILTRATE IN A MODEL OF CHRONIC RENAL ALLOGRAFT REJECTION1

A model of chronic renal rejection in the Dark-Agouti to Albino-Surgery rat combination is described. In a number of cases, the original allograft was replaced by a second Dark-Agouti allograft. Seventy-five percent of rats experienced early episodes of rejection that subsided spontaneously. Second allografts had better initial renal function. Variable degrees of tubular atrophy, interstitial fibrosis, vascular damage, glomerulosclerosis, deposition of humoral mediators, and mononuclear leukocyte infiltrate were observed in all long-term allografts. Chronic damage increased with time, and was less severe in second allografts. At 5 days, total interstitial infiltrate was similar to that seen in unmodified rejection, but there was a significant increase in CD4+ cells and a decrease in ED2 and IL-2R expression. Subsequently, the total interstitial infiltrate decreased with time, although it remained significantly higher than in isografts and residual kidneys from uninephrectomized rats. No significant decrease over time was seen in numbers of CD4+ and CD45RC+ cells. The latter had a marked focal distribution after 100 days. Total leukocyte infiltrate was similar in original and second allografts, but there were changes in the proportions of leukocyte subpopulations, including significantly lower numbers of CD45RC+ cells in the latter. The persistence of CD45RC+ cells throughout the course of chronic rejection and their lower numbers in the second allografts favors a role for these cells in the development of chronic injury. The model of chronic renal allograft rejection characterized in this study will be valuable in further studies of the mechanisms of injury in this pathology.
Proactive Straggler Avoidance using Machine Learning

The MapReduce architecture provides self-managed parallelization with fault tolerance for large-scale data processing. Stragglers, the tasks running slower than other tasks of a job, could potentially degrade the overall cluster performance by increasing the job completion time. The original MapReduce paper [1] identified that Stragglers could arise due to various reasons including software mis-configurations, hardware degradation, overloaded nodes or resource contention. Straggler mitigation techniques are mainly concentrated on being agnostic to causes behind their occurrence and spawning speculative copies to mitigate them. A fundamental unanswered question though is “what really causes stragglers? ”. Answering this question will not only open up proactive techniques to avoid stragglers by smarter scheduling, but will also give insights into the design of clusters. In this work, we analyze a production level Facebook Hadoop trace and perform regression using the node-level statistics in order to predict the task-execution times. We show that Machine Learning techniques are helpful in revealing the non-trivial correlation between task-execution times and node-level statistics such as CPU/memory utilization. We also present results of our analysis on MapReduce logs that we generated using the Berkeley cluster (icluster) with 11 nodes. Using decision tree like approach further, we show how to come up with interpretable rules that a cluster scheduler can easily use. These rules can guide the scheduler to a task assignment that avoids or minimizes the number of stragglers. Our evaluation shows that the proposed changes to scheduler cause a negligible overhead. Additionally, we also discuss observations and insights about the MapReduce framework, task execution times that we think are important. The key contributions of this work include (a) Given that existing approaches assume the correlations between nodestatus and task execution time are either too hard to find or are non-existent, we show feasibility of finding correlations and detecting stragglers using Machine Learning and (b) We propose simple modifications to the Hadoop scheduler which are easy to accommodate and are low overhead.
A Metric Suite Proposal for Logical Dependency

Logical dependencies refer to hidden interconnections among source files that are changed together in order to address an issue or change in the system. In this study we propose six metrics for logical dependency using heuristics on change time. We evaluated our proposed metrics using data from three different software companies. We also built defect prediction models with our proposed logical dependency metrics, commonly used baseline metrics, as well as combination of both. Result of our empirical studies shows that our proposed metrics are capable of capturing the characteristics of dependency among software components. It also shows the logical dependency metrics improve the performance of defect prediction models.
Impact of Land Surface Initialization on Seasonal Precipitation and Temperature Prediction

Abstract The potential role of land initialization in seasonal forecasting is illustrated through ensembles of simulations with the NASA Seasonal-to-Interannual Prediction Project (NSIPP) model. For each boreal summer during 1997–2001, two 16-member ensembles of 3-month simulations were generated. The first, “AMIP style” (Atmospheric Model Intercomparison Project) ensemble establishes the degree to which a perfect prediction of SSTs would contribute to the seasonal prediction of precipitation and temperature over continents. The second ensemble is identical to the first, except that the land surface is also initialized with “realistic” soil moisture contents through the continuous prior application (within GCM simulations leading up to the start of the forecast period) of a daily observational precipitation dataset and the associated avoidance of model drift through the scaling of all surface prognostic variables. A comparison of the two ensembles shows that land initialization has a statistically signifi.