Miracle-dz/UniFAR-FTUs huggingface dataset:
Modification in the design of small wind turbine to increase power output

The global electrical energy consumption is still rising and there is an urgent demand to increase the power capacity. It is expected that power capacity has to be doubled within 20 years. The generation, transmission/distribution and use of electrical energy should be as efficient as possible. It has been found that if we save 1KW of energy at the end-user, 6KW is saved at the generation end. This calls for provision of incentives to save energy at the end-user. Deregulation of energy in the past lowered the investment in larger power plants, which establishes the need for new power sources in near future. Two major technologies play an important role to solve the future problems. (1) Use of renewable sources of energy. (2) Use of efficient power electronics in power generation, power transmission/distribution and end-user applications. This paper deals with one of the most emerging renewable sources, wind energy, which plays an important role in energy sector. With the use of proposed venturi tube design for small wind turbines proposed in this paper, the output of the wind turbine can be substantially enhanced.
Advertising and Welfare

This paper applies conventional welfare-theoretic methods to study advertising which changes consumer tastes. In a wide range of empirically plausible circumstances, private profitability is seen to be necessary but not sufficient for the social desirability of a small amount of advertising. The market equilibrium level of such advertising is shown to be socially excessive, even when postadvertising tastes are used as the standard for welfare judgments and the monopoly profits resulting from the advertising are included in welfare. Settings of monopoly, oligopoly, and monopolistic competition are examined, and the contention that advertising is excessive is found to be strengthened at each stage.
Genetic Relatedness of the Streptococcus pneumoniae Capsular Biosynthetic Loci

ABSTRACT Streptococcus pneumoniae (the pneumococcus) produces 1 of 91 capsular polysaccharides (CPS) that define the serotype. The cps loci of 88 pneumococcal serotypes whose CPS is synthesized by the Wzy-dependent pathway were compared with each other and with additional streptococcal polysaccharide biosynthetic loci and were clustered according to the proportion of shared homology groups (HGs), weighted for the sequence similarities between the genes encoding the shared HGs. The cps loci of the 88 pneumococcal serotypes were distributed into eight major clusters and 21 subclusters. All serotypes within the same serogroup fell into the same major cluster, but in six cases, serotypes within the same serogroup were in different subclusters and, conversely, nine subclusters included completely different serotypes. The closely related cps loci within a subcluster were compared to the known CPS structures to relate gene content to structure. The Streptococcus oralis and Streptococcus mitis polysaccharide biosynthetic loci clustered within the pneumococcal cps loci and were in a subcluster that also included the cps locus of pneumococcal serotype 21, whereas the Streptococcus agalactiae cps loci formed a single cluster that was not closely related to any of the pneumococcal cps clusters.
Mobile Application Systems for Home Care: Requirements Analysis & Usage Potentials

Home care services increasingly gain importance due to demographic implications: insights on recent developments in Germany hereby relevant to industrialized countries like the USA are given. Portable application systems have only been established sporadically in German care environments unlike the comparable domain of technical field service. This paper will identify possible mobile usage scenarios by matching healthcare requirements to state-of-the-art concepts, such as productservice systems. Open potentials concerning the support of actual care processes can be concluded thereby. An integrated mobile application system can minimize knowledge deficits and enhance the quality of home care. The results are of potential relevance not only to patients and caregivers but also to different providers of healthcare or IT solutions.
Synthesis of symmetric functions using quantum cellular automata

This work presents a synthesis technique for implementing totally symmetric Boolean functions around quantum-dot cellular automata (QCA). The basic units of the design are the majority voter (majority gates) and and-or-inverter (AOI). The synthesis of a unate symmetric function is realized with majority gates only. Whereas, the general symmetric functions are realized, following the unate decomposition method, with AOI. The efficiency of proposed synthesis technique is compared with that of conventional CMOS-based designs. The simulation of benchmark functions confirms that the proposed technique results in better designs than that of CMOS based designs
Spatial discrimination in task-driven attention

Visual attention is becoming an increasingly imperative capability to endow computer vision systems and autonomous agents with. Starting from a biological inspired model of attention, we present an experiment aimed to study selective attention in 3D space. Depth has been proved to be an important feature affecting the way attention is deployed when observing a scene. We studied preferential scanning paths and fixation zones in a task-driven wandering of the tutor gaze over a scene where multiple targets had been disposed on different depth planes. We supposed that selective attention would aggregate targets in cliques that maximize utility, minimizing meanwhile visual effort produced when passing from closer planes to further planes or between different cluttered locations. By means of a purposely designed machine, we stored visual and motor data of the tutor's head; we clustered different scanning paths of the gaze shifts according to velocity and space criteria to determine a preference model of attentional shifts and fixations. We propose subsequently a utility model that can formalize acquired information and establish a vision-based attentional framework for robots. We show that an interpretation of task-driven gaze orienting based on the presented preference criteria correctly accounts for the studied behaviours, as further reported in the literature
Evidence aggregation for diagnosis: Bayesian and fuzzy strategies

This paper investigates the utility of using aggregate (average, max etc.) information in a multi-sample classification problem in terms of the accuracy of the overall classification, and the prediction of estimated error. Bayesian networks are presented here in order to allow comparison of these results with those of a previously presented fuzzy inference system. Different structures of Bayesian network are implemented, and also compared. Different methods of calculating aggregate information to append to the samples are also investigated. The authors find that appending the additional information does improve classification accuracy and lowers classification frequency. They also find that the addition of the average aggregator to the data is more effective than appending any other combination of aggregators. Lastly, they find that the naive Bayesian network structure performs better than tree-augmented Bayesian networks, as well as networks limited only in number of parents per node.
A High Performance Switchable Multiband Inductor Structure for LC-VCOs

A switchable number of turns, symmetric, parallel stacked, variable width and spacing inductor structure with performance optimized for multi-band operation and an area efficient multi-band voltage controlled oscillator circuit (VCO) are presented. The design of the proposed multi-band inductor structure and the impact of transistor switch parasitics on its quality factor performance are thoroughly discussed. The VCO circuit presented in this work is targeted towards wireless RF communication applications and operates across three frequency bands of 900 MHz, 1800 MHz, and 2.4 GHz, respectively. The VCO circuit is designed and simulated in a 0.18 um silicon on insulator process with a nominal supply voltage of 1.5 V. The presented VCO circuit achieves a phase noise performance of -104.7 dBc/Hz, -107.7 dBc/Hz, and -101.7 dBc/Hz at 1 MHz offsets from carrier frequencies 900 MHz, 1800MHz and 2.4 GHz, consuming currents of 3.8 mA, 4.5 mA, and 5.3 mA, respectively, from a 1.5 V supply.
Antioxidants selenomethionine and D-pantethine decrease the negative side effects of doxorubicin in NL/Ly lymphoma-bearing mice

Aim To investigate the potential tissue-protective effects of antioxidants selenomethionine and D-pantethine applied together with doxorubicin (Dx) on NK/Ly lymphoma-bearing mice. The impact of this chemotherapy scheme on animal survival, blood cell profile, hepatotoxicity, glutathione level, and activity of glutathione-converting enzymes in the liver was compared with the action of Dx applied alone. Methods The hematological profile of animals was studied by the analysis of blood smears under light microscopy. Hepatotoxicity of studied drugs was evaluated measuring the activity of alanine aminotransferase (ALT) and aspartate aminotransferase (AST) enzymes, De Ritis ratio, and coenzyme A fractions by McDougal assay. Glutathione level in animal tissues was measured with Ellman reagent, and the activity of glutathione reductase, transferase, and peroxidase was measured using standard biochemical assays. Results D-pantethine (500 mg/kg) and, to a lower extent, selenomethionine (600 µg/kg) partially reduced the negative side effects (leukocytopenia and erythropenia) of Dx (5 mg/kg) in NK/Ly lymphoma bearing animals on the 14th day of their treatment. This increased animal survival time from 47-48 to 60+ days and improved the quality of their life. This ability of D-pantethine and selenomethionine was realized via hepatoprotective and immunomodulating activities. D-pantethine also restored the levels of acid-soluble and free CoA in the liver of tumor-bearing animals, while selenomethionine caused the recovery of glutathione peroxidase levels in the liver, which was significantly diminished under Dx treatment. Both compounds decreased glutathione level in the liver, which was considerably induced by Dx. Conclusions Antioxidants selenomethionine and D-pantethine partially reversed the negative side effects of Dx in NK/Ly lymphoma-bearing mice and significantly increased the therapeutic efficiency of this drug in tumor treatment.
Noise tolerant selection by gaze-controlled pan and zoom in 3D

This paper presents StarGazer - a new 3D interface for gaze-based interaction and target selection using continuous pan and zoom. Through StarGazer we address the issues of interacting with graph structured data and applications (i.e. gaze typing systems) using low resolution eye trackers or small-size displays. We show that it is possible to make robust selection even with a large number of selectable items on the screen and noisy gaze trackers. A test with 48 subjects demonstrated that users who have never tried gaze interaction before could rapidly adapt to the navigation principles of StarGazer. We tested three different display sizes (down to PDA-sized displays) and found that large screens are faster to navigate than small displays and that the error rate is higher for the smallest display. Half of the subjects were exposed to severe noise deliberately added on the cursor positions. We found that this had a negative impact on efficiency. However, the user remained in control and the noise did not seem to effect the error rate. Additionally, three subjects tested the effects of temporally adding noise to simulate latency in the gaze tracker. Even with a significant latency (about 200 ms) the subjects were able to type at acceptable rates. In a second test, seven subjects were allowed to adjust the zooming speed themselves. They achieved typing rates of more than eight words per minute without using language modeling. We conclude that the StarGazer application is an intuitive 3D interface for gaze navigation, allowing more selectable objects to be displayed on the screen than the accuracy of the gaze trackers would otherwise permit.
Gerard W. Ostheimer “What’s New in Obstetric Anesthesia” Lecture

THE Society for Obstetric Anesthesia and Perinatology was founded in 1968 to provide a forum for the discus-sion of problems unique to the peripartum period. The “What’s New in Obstetric Anesthesia” Lecture was es-tablished in 1975 at the annual meeting of the society to update members of the relevant literature published in the previous calendar year. In 1995, this lecture was renamed the “Gerard Ostheimer What’s New in Obstetric Anesthesia Lecture” after the death of Gerard W. Ostheimer, M.D., an inﬂuential member of the Society for Obstetric Anesthesia and Perinatology and former Professor of Anesthesiology at Brigham and Women’s Hospital, Boston, Massachusetts. Each year, the lecturer reviews articles from obstetric anesthesia, obstetrics, and neonatology that may be important to practicing obstetric anesthesiologists. For 2005, 1,159 articles were selected and included in the 38th Annual Meeting sylla-bus. This review focuses on three areas of interest to obstetric anesthesiologists: preeclampsia, labor analgesia, and spinal anesthesia for cesarean delivery. The individual articles have been selected not only on scientiﬁc merit, but also if they have raised important issues or caused controversy.
Price and Income Elasticities of Turkish Export Demand : A Panel Data Application

In this paper, price and income elasticities of export demand are calculated. The study is extended to sectoral and country specific export demand functions. The paper presents some panel unit root and cointegration tests, which have been studied extensively in recent years. The major aim of this study is to find the price and foreign income elasticities of aggregate export demand. According to the estimation results, the real exchange rate elasticity of total export demand is found to be less than one, whereas the income elasticity is found to be greater than one.
Neuronal regulation of astroglial morphology and proliferation in vitro

To analyze the interdependence of neurons and astroglia during central nervous system development, a rapid method for purifying early postnatal cerebellar neurons and astroglia, and recombining them in vitro, has been developed. The influence of neurons on astroglial shape and proliferation has been evaluated with an in vitro model system previously used to describe the role of cerebellar astroglia in neuronal migration and positioning (Hatten, M. E., and R. K. H. Liem, 1981, J. Cell Biol., 90:622-630; and Hatten, M. E., R. K. H. Liem, and C. A. Mason, 1984, J. Cell Biol., 98:193-204. Cerebellar tissue harvested from C57Bl/6J mouse cerebellum on the third or fourth day postnatal was dissociated into a single cell suspension with trypsin, and enriched glial and neuronal fractions were separated with a step gradient of Percoll. Highly purified astroglial and neuronal fractions resulted from subsequently preplanting the cells on a polylysine-coated culture surface. In the absence of neurons, astroglia, identified by staining with antisera raised against purified glial filament protein, assumed a flattened shape and proliferated rapidly. In the absence of astroglia, cerebellar neurons, identified by staining with antisera raised against the nerve growth factor-inducible large external (NILE) glycoprotein and by electron microscopy, formed cellular reaggregates, had markedly impaired neurite outgrowth, and survived poorly. When purified neurons and isolated astroglia were recombined, astroglial proliferation slowed markedly and the flattened shape expressed in the absence of neurons transformed into highly elongated profiles that resembled embryonic forms of cerebellar astroglia. After longer periods (48-72 h) in the presence of neurons, astroglia had "Bergmann-like" or "astrocyte-like" shapes and neurons commonly associated with them. These results suggest that neurons influence the differentiation of astroglia.
The Importance of Feature Representation for Visual Tracking Systems with Discriminative Methods

Visual tracking has been a challenging problem in the field of computer vision due to a variety of appearance changes of target object, while it is a widely explored area, with many applications in human-computer interaction, surveillance and robotics. Recently thanks to a great progress made by machine learning researchers, more and more sophisticated techniques have been applied to visual tracking. In that case, the tracking task is easily translated into a binary classification problem. Based on this framework, In this paper we investigate the influence of different feature representations on the performance of a tracker by designing controlled experiments. Finally, we find that feature representation plays a crucial role in a visual tracking system. Additionally, although the complex model learning algorithm is the focus of many attentions and studies, our experiments indicate that a good feature representation is much more important than using a complex classification algorithm in a visual tracking system. We believe that our work will provide a fresh perspective for the research of visual tracking which can dramatically improve tracking performances.
Probability on graphs

The random assignment problem is to minimize the cost of an assignment in a n×n matrix of random costs. In this paper we study this problem for some integer valued cost distributions. We consider both uniform distributions on 1, 2, . , m, for m = n or n, and random permutations of 1, 2, . , n for each row, or of 1, 2, . , n for the whole matrix. We find the limit of the expected cost for the n cases, and prove bounds for the n cases. This is done by simple coupling arguments together with Aldous recent results for the continuous case. We also present a simulation study of these cases.
A new paradigm of ranking & searching in learning object repository

With the development of internet and search engine, users are thought to obtain everything through corresponding web services. Although general purpose searching such as one provided by Google is powerful, searching mechanism for different purposes has to rely on specific metadata. We followed SCORM and CORDRA to develop a registry system named MINE Registry for storing and managing the learning objects. As a contribution, we propose the concept of "Reusability Tree" to represent the relationships among relevant Learning Objects and to enhance CORDRA. We further collect relevant information while users are utilizing Learning Objects, such as citations and time period persisted. The feedbacks from community users are also considered as critical elements for evaluating significance degree of Learning Objects. Through these factors, we propose a mechanism to weight and rank Learning Objects in the MINE Registry, in addition to other external learning objects repositories.
The Use of Distributed Processing and Cloud Computing in Agricultural Decision-Making Support Systems

One of the main challenges in agriculture is to sustainably meet the demand for food while preserving natural resources for future productions. Information Technology can assist producers to make better decisions by providing them with data and tools that enhance decision-making process, consequently allowing better management of the natural resources. Cloud-computing platforms and the extraction of data available on public weather related data sets allow the development of web applications that can assist producers with their investing and planning decisions. This paper describes the Big Weather solution, an agricultural decision-making support system that utilizes a cloud-computing platform, distributed processing technologies, and a big data framework. This paper also presents Big Weather architecture and an example of metric calculations (average temperature and humidity) and discusses the performance of the solution when tested in different virtual machine scenario configurations. The novelty is the transparency of the framework, which allows farmers to make better decisions based on data available on the cloud.
Development of an in vitro Assay, Based on the BioFilm Ring Test®, for Rapid Profiling of Biofilm-Growing Bacteria

Microbial biofilm represents a major virulence factor associated with chronic and recurrent infections. Pathogenic bacteria embedded in biofilms are highly resistant to environmental and chemical agents, including antibiotics and therefore difficult to eradicate. Thus, reliable tests to assess biofilm formation by bacterial strains as well as the impact of chemicals or antibiotics on biofilm formation represent desirable tools for a most effective therapeutic management and microbiological risk control. Current methods to evaluate biofilm formation are usually time-consuming, costly, and hardly applicable in the clinical setting. The aim of the present study was to develop and assess a simple and reliable in vitro procedure for the characterization of biofilm-producing bacterial strains for future clinical applications based on the BioFilm Ring Test® (BRT) technology. The procedure developed for clinical testing (cBRT) can provide an accurate and timely (5 h) measurement of biofilm formation for the most common pathogenic bacteria seen in clinical practice. The results gathered by the cBRT assay were in agreement with the traditional crystal violet (CV) staining test, according to the κ coefficient test (κ = 0.623). However, the cBRT assay showed higher levels of specificity (92.2%) and accuracy (88.1%) as compared to CV. The results indicate that this procedure offers an easy, rapid and robust assay to test microbial biofilm and a promising tool for clinical microbiology.
A Collaborative Filtering Recommender using SOM clustering on Keywords Joel Bennett November

This project comprises designing and implementing a hybrid recommender system for web–pages which uses data from a social tagging system to recommend interesting items to users. For the initial implementation, the tagging data will come from del.icio. us, the oldest and largest public social bookmarking system. The system will cluster items using a self–organizing maps (SOM) network and will include a new SOM visualizer that allows users to see and modify the system’s evaluation of their regions of interest. The focus of the programming project will be a scraper for gathering tagged URLs from del.icio. us, a visualizer, and the recommender. The SOM network code will be based on existing implementations, and two recommenders will be built, with one using a single map for URLs and users and the other using separate maps to compare the relative quality of the recommendations.