Miracle-dz/UniFAR-FTUs huggingface dataset:
Short-term wind speed forecasting using Support Vector Machines

Wind speed forecasting has been becoming an important field of research to support the electricity industry mainly due to the increasing use of distributed energy sources, largely based on renewable sources. This type of electricity generation is highly dependent on the weather conditions variability, particularly the variability of the wind speed. Therefore, accurate wind power forecasting models are required to the operation and planning of wind plants and power systems. A Support Vector Machines (SVM) model for short-term wind speed is proposed and its performance is evaluated and compared with several artificial neural network (ANN) based approaches. A case study based on a real database regarding 3 years for predicting wind speed at 5 minutes intervals is presented.
Comparing Performance of Text Summarization Methods on Polish News Articles

This paper presents the goals, results and conclusions from an experiment where several shallow text summarization methods have been applied to news articles written in Polish. Specifically, we focused on various techniques of salient sentence selection as these algorithms are most popular in the English-spoken world and are highly efficient in practice. The quality of automatically generated summaries was evaluated by comparing them against a reference set of man-made summaries. This reference set of summaries is a valuable resource on its own as it comes from an unrestricted survey where user groups from different backgrounds had been asked to select “most appropriate” sentences to form a summary.
High resolution analysis of the secretory pathway in mammotrophs of the rat anterior pituitary

The secretory process in pituitary mammotrophs was analyzed by quantitative electron microscope autoradiography. Dispersed pituitary cells from estrogen-treated female rats were subjected to pulse- labeling with [3H]leucine (5 min) followed by a chase incubation of up to 4 h. Autoradiograms were prepared using fine-grained emulsion (Kodak 129-01), and analyzed using a three-step "mask analysis' procedure: (a) the distribution of autoradiographic grains is determined as in a simple grain density analysis; (b) masks (transparent overlays) are used to generate expected grains from assumed sources; and (c) a computer program compares these two distributions and varies the expected distribution to match the observed distribution, thereby identifying the radioactive sources in the tissue. The overall route of intracellular transport of prolactin from rough endoplasmic reticulum (ER) leads to Golgi complex leads to immature secretory granules leads to mature secretory granules was as established in previous studies. However, by use of the high resolution emulsion and method of analysis, the precision with which label could be localized within individual source compartments was much greater and the time resolution was much sharper than achieved previously using Ilford L4 emulsion and simple grain density analysis. The main new findings were as follows: (a) the ER was essentially drained of radioactivity by 30 min, the Golgi complex by 1 h, and the immature secretory granules by 2h postpulse. This indicates that the secretory product (prolactin) is rapidly and efficiently transported out of these compartments. (b) approximately 30% of the total radioactivity remains located in the ground cytoplasm over the entire postpulse period examined (up to 4 h), and by 30 min postpulse the grain density in the ground cytoplasm exceeded that of the ER. This indicates the ability to resolve ER-associated label (presumably associated mainly with secretory products) from the cytoplasmic label (presumably associated with nonsecretory proteins). (c) the specific activity of immature secretory granules was much greater than previously appreciated; at 1 h postpulse it was greater than 200 times that of the adjacent Golgi complex cisternae. This large dynamic range in observed grain density demonstrates the ability to effectively correct for radiation spread and thus to detect with great accuracy high concentration of label even from very small structures (20-100 nm) which constitute a small percentage (less than 1%) of the total cell area.
SQL Injection detection using machine learning

In the present world, the web is the firmest and most common medium of communication and business interchange. Every day, millions of data are loaded through various channels on the web by users and user input can be malicious. Therefore, security becomes a very important aspect of web applications. Since they are easily accessible, they are prone to many vulnerabilities which if neglected can cause harm. The attackers make use of these loopholes to gain unauthorized access by performing various illegal activities. SQL Injection is one such attack which is easy to perform but difficult to detect because of its varied types and channel. This may result in theft, leak of personal data or loss of property. In this paper we have analyzed the existing solutions to the problems such as AMNESIA [1] and SQLrand [3] and their limitations. We have devised a classifier for detection of SQL Injection attacks. The proposed classifier uses combination of Naïve Bayes machine learning algorithm and Role Based Access Control mechanism for detection. The proposed model is tested based on the test cases derived from the three SQLIA attacks: comments, union and tautology.
Kainic acid alters the metabolism of Met5-enkephalin and the level of dynorphin A in the rat hippocampus

Male Fischer-344 rats were given a single intrastriatal injection of kainic acid (KA; 1 microgram/rat), which caused recurrent motor seizures lasting 3–6 hr. During the convulsive period, native Met5- enkephalin-like (ME-LI) and dynorphin A (1–8)-like (DYN-LI) immunoreactivities in hippocampus decreased by 31 and 63%, respectively. By 24 hr after dosing, the hippocampal opioid peptides had returned to control levels, and by 48 hr ME-LI had increased 270% and DYN-LI 150%. Immunocytochemical analysis revealed that ME-LI and Leu5-enkephalin-like (LE-LI) immunostaining in the mossy fibers of dentate granule cells and the perforant-temporoammonic pathway had decreased visibly by 6 hr and had increased markedly by 48 hr following KA. A visible decrease in DYN-LI in mossy fiber axons within 6 hr was followed by a substantial increase by 48 hr. To determine whether the increases in hippocampal ME-LI reflected changes in ME biosynthesis, levels of mRNA coding for preproenkephalin (mRNAenk) and cryptic ME-LI cleaved by enzyme digestion from preproenkephalin were measured. Following the convulsive period (6 hr), mRNAenk was 400% of control, and by 24 hr, cryptic ME-LI was 300% of control. Increases in native and cryptic ME-LI and in mRNAenk were also noted in entorhinal cortex, but not in hypothalamus or uninjected striatum. Our data suggest that KA-induced seizures cause an increase in ME release, followed by a compensatory increase in ME biosynthesis in the hippocampus and entorhinal cortex.
Effects of Iron Deficiency on Iron Binding and Internalization into Acidic Vacuoles in Dunaliella salina1[W][OA]

Uptake of iron in the halotolerant alga Dunaliella salina is mediated by a transferrin-like protein (TTf), which binds and internalizes Fe3+ ions. Recently, we found that iron deficiency induces a large enhancement of iron binding, which is associated with accumulation of three other plasma membrane proteins that associate with TTf. In this study, we characterized the kinetic properties of iron binding and internalization and identified the site of iron internalization. Iron deficiency induces a 4-fold increase in Fe binding, but only 50% enhancement in the rate of iron uptake and also increases the affinity for iron and bicarbonate, a coligand for iron binding. These results indicate that iron deprivation leads to accumulation and modification of iron-binding sites. Iron uptake in iron-sufficient cells is preceded by an apparent time lag, resulting from prebound iron, which can be eliminated by unloading iron-binding sites. Iron is tightly bound to surface-exposed sites and hardly exchanges with medium iron. All bound iron is subsequently internalized. Accumulation of iron inhibits further iron binding and internalization. The vacuolar inhibitor bafilomycin inhibits iron uptake and internalization. Internalized iron was localized by electron microscopy within vacuolar structures that were identified as acidic vacuoles. Iron internalization is accompanied by endocytosis of surface proteins into these acidic vacuoles. A novel kinetic mechanism for iron uptake is proposed, which includes two pools of bound/compartmentalized iron separated by a rate-limiting internalization stage. The major parameter that is modulated by iron deficiency is the iron-binding capacity. We propose that excessive iron binding in iron-deficient cells serves as a temporary reservoir for iron that is subsequently internalized. This mechanism is particularly suitable for organisms that are exposed to large fluctuations in iron availability.
Two‐dimensional hydrodynamic simulation of an accretion flow with radiative cooling in a close binary system

Two-dimensional numerical simulations of an accretion flow in a close binary system are performed by solving the Euler equations with radiative transfer. In the present study, the specific heat ratio is assumed to be constant while the radiative cooling effect is included as a non-adiabatic process. The cooling effect of the disc is considered by discharging energy in the vertical directions from the top and bottom surfaces of the disc. We use the flux-limited diffusion approximation to calculate the radiative heat flux values. Our calculations show that a disc structure appears and spiral shocks are formed on the disc. These features are similar to those observed in the case of an adiabatic gas with a lower specific heat ratio, y = 1.01. It is found that, when the radiative cooling effect is accounted for, the mass of the disc becomes larger than that assuming y = 5/3, and smaller than that assuming y = 1.01. We conclude that employing an adiabatic gas with a lower specific heat ratio is almost a valid assumption for simulating an accretion disc with the radiative cooling effect.
Spatial dynamic factor analysis

A new class of space-time models derived from standard dynamic factor models is proposed. The temporal dependence is modeled by latent factors while the spatial dependence is modeled by the factor loadings. Factor analytic arguments are used to help identify temporal components that summarize most of the spatial variation of a given region. The temporal evolution of the factors is described in a number of forms to account for different aspects of time variation such as trend and seasonality. The spatial dependence is incorporated into the factor loadings by a combination of deterministic and stochastic elements thus giving them more flexibility and generalizing previous approaches. The new structure implies nonseparable space-time variation to observables, despite its conditionally independent nature, while reducing the overall dimensionality, and hence complexity, of the problem. The number of factors is treated as another unknown parameter and fully Bayesian inference is performed via a reversible jump Markov Chain Monte Carlo algorithm. The new class of models is tested against one synthetic dataset and applied to pollution data obtained from the Clean Air Status and Trends Network (CASTNet). Our factor model exhibited better predictive performance when compared to benchmark models, while capturing important aspects of spatial and temporal behavior of the data.
Examining Utilitarian and Hedonic Factors and their Moderators for Virtual World Collaborations

Although experts sense a big future for virtual worlds (VWs) in the workplace scenario, their use in the business world is still in a nascent stage. A key challenge for organizations is to motivate users for utilizing VW for workplace related tasks. This research investigates the behavioral intention (BI) to use VW as a workplace ‘collaboration tool’. The model, grounded in literature on ‘motivations’ and ‘task success characteristics’, not only examines the direct effects of ‘utilitarian’ and ‘hedonic’ factors on VW usage intentions but also the moderating role of ‘familiarity’ and ‘control’. Results suggest a salient role of ‘utilitarian’ as compared to ‘hedonic’ factors and demonstrate the importance of considering the moderating effects of ‘familiarity’ and ‘control’ in determining the intention to use VW for collaborations. Implications for research and practice are also discussed.
Siddhi: a second look at complex event processing architectures

Today there are so much data being available from sources like sensors (RFIDs, Near Field Communication), web activities, transactions, social networks, etc. Making sense of this avalanche of data requires efficient and fast processing. Processing of high volume of events to derive higher-level information is a vital part of taking critical decisions, and Complex Event Processing (CEP) has become one of the most rapidly emerging fields in data processing. e-Science use-cases, business applications, financial trading applications, operational analytics applications and business activity monitoring applications are some use-cases that directly use CEP. This paper discusses different design decisions associated with CEP Engines, and proposes some approaches to improve CEP performance by using more stream processing style pipelines. Furthermore, the paper will discuss Siddhi, a CEP Engine that implements those suggestions. We present a performance study that exhibits that the resulting CEP Engine--Siddhi--has significantly improved performance. Primary contributions of this paper are performing a critical analysis of the CEP Engine design and identifying suggestions for improvements, implementing those improvements through Siddhi, and demonstrating the soundness of those suggestions through empirical evidence.
What makes memory constructive? A study in the serial reproduction of Bartlett’s experiments

The claim that memory is constructive or reconstructive is no longer controversial in psychology. However, in the last decades it has generally been taken to mean that our memories are inaccurate or distorted. In the locus classicus of the constructive memory idea—Bartlett’s Remembering—we find a different meaning: Constructive is there understood as a future-oriented and adaptive characteristic of remembering, which can also lead to accuracy. His notion of constructiveness was even earlier elaborated in relation to group dynamics in his book Psychology and Primitive Culture. How did we get from one meaning of constructive to another? This question is explored through a serial reproduction analysis of experiments purporting to replicate Bartlett’s study. The focus is on the transformation of terminology used to describe qualitative changes introduced by subjects into reproductions. In this history a diversity of terms, coming from different intellectual sources, is gradually subsumed under the single term ‘distortion’. Thus, psychologists have reconstructed Bartlett’s work based on their own background, other influences and their own project for the discipline, illustrating the very constructive processes Bartlett theorized.
Comparative study on the osseointegration of implants in dog mandibles according to the implant surface treatment

Objectives This study compared the impact of implant surface treatment on the stability and osseointegration of implants in dog mandibles. Materials and Methods Six adult dogs received a total of 48 implants that were prepared using four different surface treatments; resorbable blast media (RBM), hydroxyapatite (HA), hydrothermal-treated HA, and sand blasting and acid etching (SLA). Implants were installed, and dogs were separated into 2- and 4-week groups. Implant stability was evaluated via Periotest M, Osstell Mentor, and removal torque analyzers. A histomorphometric analysis was also performed. Results The stability evaluation showed that all groups generally had satisfactory values. The histomorphometric evaluation via a light microscope revealed that the HA surface implant group had the highest ratio of new bone formation on the entire fixture. The hydrothermal-treated HA surface implant group showed a high ratio of bone-to-implant contact in the upper half of the implant area. Conclusion The hydrothermal-treated HA implant improved the bone-to-implant contact ratio on the upper fixture, which increased the implant stability.
A Survey on the Model Theory of Difference Fields

We survey the model theory of difference fields, that is, fields with a distinguished automorphism σ. After introducing the theory ACFA and stating elementary results, we discuss independence and the various concepts of rank, the dichotomy theorems, and, as an application, the Manin–Mumford conjecture over a number field. We conclude with some other applications. Difference field are fields with a distinguished automorphism σ. They were first studied by Ritt in the 1930s. A good reference for the algebraic results is [Cohn 1965]. Interest in the model theory of difference fields started at the end of the eighties, particularly during the MSRI logic year, because of two questions. The first question stemmed from the failure of Zil’ber’s conjecture: there is a strongly minimal theory extending the theory of algebraically closed fields of any given characteristic. People were looking at the possibility of finding a nondefinable automorphism σ of F p (the algebraic closure of the field Fp with p elements), such that Th(F p ,+ , · , σ) is strongly minimal. This question so far remains open. The second problem had to do with the difference fields Fq = (F p ,+ , · , φq), where q is a power of p and φq : x 7→ x is a power of the Frobenius automorphism x 7→ x. The hope was to generalise the work of Ax on finite fields to these structures, and in particular to describe the theory of the non-principal ultraproducts of the difference fields Fq. These questions led Macintyre, van den Dries and Wood to look for a model companion of the theory of difference fields, and to prove various results (decidability, description of the completions, etc . . . ) for this theory, henceforth called ACFA. For details and attribution of results, see [Macintyre 1997]. I should also mention that the second problem was solved recently, by Hrushovski [1996b] and Notes based on lectures given at MSRI, January 98.
An integrated approach to discover tag semantics

Tag-based systems have become very common for online classification thanks to their intrinsic advantages such as self-organization and rapid evolution. However, they are still affected by some issues that limit their utility, mainly due to the inherent ambiguity in the semantics of tags. Synonyms, homonyms, and polysemous words, while not harmful for the casual user, strongly affect the quality of search results and the performances of tag-based recommendation systems. In this paper we rely on the concept of tag relatedness in order to study small groups of similar tags and detect relationships between them. This approach is grounded on a model that builds upon an edge-colored multigraph of users, tags, and resources. To put our thoughts in practice, we present a modular and extensible framework of analysis for discovering synonyms, homonyms and hierarchical relationships amongst sets of tags. Some initial results of its application to the delicious database are presented, showing that such an approach could be useful to solve some of the well known problems of folksonomies.
Absorbing aerosol in the troposphere of the Western Arctic during the 2008 ARCTAS/ARCPAC airborne field campaigns

In the spring of 2008 NASA and NOAA funded the ARCTAS and ARCPAC field campaigns as contribu- tions to POLARCAT, a core IPY activity. During the cam- paigns the NASA DC-8, P-3B and NOAA WP-3D aircraft conducted over 160 h of in-situ sampling between 0.1 and 12 km throughout the Western Arctic north of 55 N (i.e. Alaska to Greenland). All aircraft were equipped with mul- tiple wavelength measurements of aerosol optics, trace gas and aerosol chemistry measurements, as well as direct mea- surements of the aerosol size distributions and black car- bon mass. Late April of 2008 proved to be exceptional in terms of Asian biomass burning emissions transported to the Western Arctic. Though these smoke plumes account for only 11-14 % of the samples within the Western Arc- tic domain, they account for 42-47 % of the total burden of black carbon. Dust was also commonly observed but only contributes to 4-12 % and 3-8 % of total light absorption at 470 and 530 nm wavelengths above 6 km. Below 6 km, light absorption by carbonaceous aerosol derived from ur- ban/industrial and biomass burning emissions account for 97-99 % of total light absorption by aerosol. Stratifying the data to reduce the influence of dust allows us to determine mass absorption efficiencies for black carbon of 11.2 ±0.8, 9.5±0.6 and 7.4±0.7 m 2 g 1 at 470, 530 and 660 nm wave-
Institutional Investors and Corporate Investment

This paper investigates whether institutional investors influence firms’ investment policies. By virtue of their significant ownership stakes and investment horizons, long-term institutional investors should closely monitor management and thus reduce agency conflicts in investment choices. Using a panel dataset of 2,511 U.S. manufacturing firms that went public between 1980 and 2003, I find that firms with long-term institutional investors tend to have lower capital expenditure than widely-held firms. Investment is reduced precisely in firms that are more exposed to the danger of over-investment: (a) firms that invest too much after controlling for their growth opportunities, financing constraints and industry affiliation, and (b) firms that have few investment opportunities but large cash flows. Most importantly, a reduction in capital expenditure in these firms leads to higher subsequent firm profitability and stock market performance, confirming that institutional investors’ actions aimed at removing over-investment are value-enhancing.
Protein Phosphatase 2A Facilitates Axonogenesis by Dephosphorylating CRMP2

Protein phosphatase 2A (PP2A) is indispensable in development, and deficits of PP2A and deterioration of neuronal axons have been observed in several neurodegenerative disorders, but the direct link between PP2A and the neuronal axon development is still missing. Here, we show that PP2A is essential for axon development in transfected rat brain and the dissociated hippocampal neurons. Upregulation of PP2A catalytic subunit (PP2Ac) not only promotes formation and elongation of the functional axons but also rescues axon retardation induced by PP2A inhibition. PP2A can dephosphorylate collapsin response mediator protein-2 (CRMP2) that implements the axon polarization, whereas constitutive expression of phosphomimic-CRMP2 abrogates the effect of PP2A upregulation. We also demonstrate that PP2Ac is enriched in the distal axon of the hippocampal neurons. Our results reveal a mechanistic link between PP2A and axonogenesis/axonopathy, suggesting that upregulation of PP2A may be a promising therapeutic for some neurodegenerative disorders.