Miracle-dz/UniFAR-FTUs huggingface dataset:
Automated Detection of Spammers ’ Profiles using Improved K-Means in Twitter

In the digital world of applications, a new application called twitter made a major impact in online social networking and micro blogging. The communication between users is through text based post. Its popularity also attracts many spammers to infiltrate legitimate users account with large amount of spam messages . Online social networking platforms are providing us with a large scale platform to study the human behavior. This paper improves K Means algorithm to separate human from not human users in order to identify normal human activity. K-Means is one of the simplest unsupervised learning algorithms that solve the well known clustering problem. Here in this research paper in order to achieve the target results with better accuracy, an efficient approach will be designed by modifying sequential K-Means clustering algorithm to detect spam in Twitter. The data which has been provided for the entire process to be performed is extracted from the social networking website Twitter with the help of R Package as it provides interface with the Twitter web API (Application Programmable Interface). Various calculations has been performed to calculate the accuracy, precision, and recall and based on these results and respective graphs have been obtained.
Envisioning and Enabling Sustainable Smart Markets

__Abstract__ Many of the world’s most urgent problems such as climate change, population growth, poverty, malnutrition and environmental degradation not only demand solutions but also require us to find more sustainable ways of living. Market mechanisms can be effective in solving large-scale resource allocation problems of this kind, but only if the market design reflects the social costs. The growth and spread of advanced information and communication technologies mean that new smart markets offer a way to achieve this and will become central to many areas of economic activity. However, the volumes of data and speed of transactions involved place a burden on human decisionmaking capabilities, and information systems can have a central role to play in helping to devise solutions – in particular, in developing intelligent software agents to provide decision support. This address looks at the challenges and opportunities involved for information systems researchers, and sets out an agenda for sustainable smart markets research, centered on collaborative approaches. It focuses on three overlapping areas: market and learning agent design; market evaluation using autonomous learning agents; and real-time decision support. Examples are included of current work on sustainable smart markets for electricity (smart grid) and for flowers (Dutch Flower Auctions).
Minimum variance control structure for adaptive optics systems

This paper shows that the minimum variance adaptive optics controller under nearly ideal conditions is the integral controller used in adaptive optics systems. The inputs to the controller dynamics are obtained from a MAP reconstructor that uses the estimation error covariance of the wavefront error. The conditions assumed to obtain this controller are: isotropic first-order (but non-stationary) temporal atmospheric aberrations; no loop delay; and no deformable mirror dynamics.
Fiber Bragg gratings in small-core Ge-Doped photonic crystal fibers

We report about fiber Bragg gratings (FBGs) inscribed in a small-core Ge-doped photonic crystal fibers with a UV laser and a Talbot interferometer. We systematically investigated the responses of such FBGs to temperature, strain, bending, and transverse-loading. The Bragg wavelength of the FBGs shifts toward longer wavelengths with increasing temperature, tensile strain, and transverse-loading. The bending and transverse-loading properties of the FBGs depend strongly on the fiber orientations.
Chinese Geographical Knowledge Entity Relation Extraction via Deep Neural Networks

Aiming at the problem of complex relation pattern and low relation extraction precision in the unstructured free text, in this paper, a novel extraction model for Chinese geographical knowledge relation extraction using a real end-to-end deep neural networks (DNNs) is proposed. The proposed method is a fusion DNNs consisting of one convolutional neural networks and two neural networks, which contains word feature, sentence feature and class feature. For the experiments, we construct geographic entity relation type system and corpus. We achieve a good performance with the averaged overall precision of 96.54%, averaged recall of 92.99%, and averaged F value of 94.56%. Experimental results confirm the superiority of the proposed Chinese geographical knowledge relation extraction method. The data of this paper can be obtained from http://nlp.webmeteor. cn.
Coherent Energy Exchange in the Strong Coupling Limit of the Lossy Spin-Boson Model

We focus on the lossy spin-boson model since it is capable of efficient energy exchange between two-level systems and an oscillator under conditions where the characteristic energy of the oscillator is small compared to the transition energy of the two-level systems. We are considering this model as the essential component for a theoretical understanding of the excess heat effect in the Fleischmann– Pons experiment. We introduce an iterative algorithm that allows the numerical calculation of eigenfunctions and eigenvalues of the coefficient eigenvalue equation that arises in the local approximation. From systematic calculations in the strong coupling limit we establish scaling laws for the self-energy and for the indirect coupling matrix element in the local approximation. These results are used to study the system dynamics for simple strong coupling models. © 2011 ISCMNS. All rights reserved.
Scaling Up Simultaneous Diagonalization

Simultaneous matrix diagonalization is a key subroutine in many machine learning problems, including blind source separation and parameter estimation in latent variable models. Here, we extend joint diagonalization algorithms to low-rank and asymmetric matrices and also provide extensions to the perturbation analysis of these methods. Our results allow joint diagonalization to scale to larger problem sizes and to new domains; we give a survey of such applications and report improvements relative to the state-of-the-art on a latent variable learning task. We hope that our results will demonstrate the usefulness and versatility of joint diagonalization as a tool in optimization and machine learning.
Relating physico-chemical properties of frozen green peas ( Pisum sativum L . ) with sensory quality Sensory and physico-chemical properties of frozen green peas

BACKGROUND: The acceptability of frozen green peas depends on their sensory quality. There is a need to relate physico-chemical parameters to sensory quality. In this research, six brands of frozen green peas representing product sold for retail and caterer’s markets were purchased and subjected to descriptive sensory evaluation and physico-chemical analyses (including dry matter content, alcohol insoluble solids content, starch content, °Brix, residual peroxidase activity, size sorting, hardness using texture analysis and colour measurements) to assess and explain product quality. RESULTS: The sensory quality of frozen green peas, particularly texture properties, were well explained using physico-chemical methods of analysis notably alcohol insoluble solids, starch content, hardness and °Brix. Generally, retail class peas were of superior sensory quality to caterer’s class peas although one caterer’s brand was comparable to the retail brands. Retail class peas were sweeter, smaller, greener, more moist and more tender than the caterer’s peas. Retail class peas also had higher °Brix, a*, hue and chroma values; lower starch, alcohol insoluble solids, dry matter content and hardness measured. CONCLUSIONS: The sensory quality of frozen green peas can be partially predicted by measuring physico-chemical parameters particularly °Brix and to a lesser extent hardness by texture analyser, alcohol insoluble solids, dry matter and starch content.
Measuring Spillovers from Alternative Forms of Foreign Investment

Much of the endogenous growth literature has dwelled on evaluating the spillover effects of trade on growth, but much less efforts have been directed towards tracing and quantifying the spillover effects of foreign investments. This paper, in incorporating the effects of various types of foreign investments, namely foreign direct investment (FDI), foreign portfolio investment (FPI) and other foreign investment (OFI) fills this gap in the literature. Adopting the stochastic frontier approach, this paper constructs an OECD frontier based on a panel dataset of 20 OECD countries over the 1981-2000 period. Spillover effects of FDI, FPI, OFI and trade are gauged by their respective contributions towards reducing technical inefficiencies, which are represented by the distance of each country from the constructed frontier. Results from the multiple models examined in the paper indicate that inflows of foreign investment and trade have been instrumental in reducing inefficiencies across OECD countries, whereas outflows of foreign investment exacerbate inefficiencies. The study also confirms some previous findings that the spillover effects of FDI inflows are larger than that of trade but does not find evidence in favour of the view that the spillover effects of trade are overestimated when FDI flows are excluded from the analysis. Moreover, the impact of FDI inflows is larger than those of FPI and OFI inflows. The importance of absorptive capacities of host economies in capturing spillover gains from FDI inflows is also examined. Amongst the various measures of absorptive capacity considered, only human capital was found to be important.
Dual-band textile hexagonal artificial magnetic conductor for WiFi wearable applications

A novel dual-band textile hexagonal AMC design covering the entire 2.5/5.5 GHz WiFi bands for wearable applications is presented through FEM simulations and reflection coefficient phase measurements in anechoic chamber. The designed structure shows polarization-angle independence under normal incidence and its angular stability under oblique incidence is also analyzed.
Reliability and Validity of Useful Field of View Test Scores as Administered by Personal Computer

The Useful Field of View test (UFOV 1 ) is a measure of processing speed that predicts driving performance and other functional abilities in older adults. In comparison to a number of other visual and cognitive measures, the UFOV measure has consistently been found to be the strongest predictor of motor vehicle crashes of older adults. This measure has valuable applications in that computerized, performance-based measures that are predictive of crashes in the elderly population can provide an objective criterion for determining the need for driver restriction or rehabilitation. Administration of the UFOV test has evolved from the standard version (administered via touch-screen with the Visual Attention Analyzer) to two briefer versions, which are administered on a personal desktop computer (PC) using either a touch screen or mouse response option. These new versions of the test are briefer and require less specialized equipment, making the test more portable and practical for use in clinical settings. This study examined the reliability and validity of the scores from these two new versions. Results indicate that test-retest reliabilities of the scores from the UFOV PC versions are high (r's= 0 .884 for mouse and 0.735 for touch), and performance on both PC versions correlates well with performance on the standard version (r's = 0.658 for mouse and 0.746 for touch). Furthermore, scores were highly correlated (r = 0.916) when participants used either a touch screen or a mouse to input responses. In conclusion, the reliability and validity coefficients are of sufficient magnitude to make the touch and mouse PC versions of the UFOV practical for use in clinical evaluations. UFOV is a registered trademark of Visual Awareness, Inc., Chicago, IL
Stimulation of preadipocyte differentiation by steroid through targeting of an HDAC1 complex

Glucocorticoids potentiate the early steps of preadipocyte differentiation and promote obesity in Cushing's syndrome and during prolonged steroid therapy. We show that glucocorticoids stimulate 3T3 L1 preadipocyte differentiation through a non‐transcriptional mechanism mediated through the ligand‐binding domain of the glucocorticoid receptor. This enhanced the onset of CCAAT/enhancer binding protein (C/EBPα) expression by potentiating its initial transcriptional activation by C/EBPβ. In the absence of steroid, C/EBPβ associated with a transcriptional corepressor complex containing mSin3A and histone deacetylase 1 (HDAC1), but lacking HDAC2 and RbAp46/48. HDAC1/mSin3A were recruited to the C/EBPα promoter with C/EBPβ and promoted the deacetylation of histone H4. Steroid induced the specific depletion of this corepressor by targeting the HDAC1 within the complex for degradation through the 26S proteasome. Treatment with histone deacetylase inhibitors replaced the effects of steroid treatment on preadipocyte differentiation and C/EBPα expression, while overexpression of HDAC1 abrogated the stimulatory effects of steroid. Recapitulation of the glucocorticoid effect by progestin treatment in the presence of the progesterone receptor ligand‐binding domain suggests a conserved mechanism relevant to many aspects of steroid‐mediated differentiation.
Business R&D Expenditure and Capital in Europe

This study presents new estimates of business R&D capital stocks for 22 countries at the aggregate and industry levels. At 9 percent of GDP, the EU business R&D capital stock falls short of its US and Japanese counterparts. Within the EU, R&D capital stocks are much lower in the southern and the new member states, reflecting large and persistent disparities in R&D expenditure. There was hardly any convergence over the past decade. The R&D capital stock is concentrated on three technologyintensive manufacturing industries and is positively correlated with growth in total factor productivity across countries and industries. Finally, the ratios between the stocks of R&D capital and tangible capital suggest marked differences in how R&D and tangible capital are combined in production.
The Construction of a Corporate Governance Rating System for a Small Open Capital Market: Methodology and Applications in the Greek Market

The need of institutional investors to evaluate the corporate governance (CG) practices of the listed companies resulted in many attempts to construct CG rating methodologies. This paper, in response to this situation, presents an attempt to quantify the compliance of large capitalisation Greek companies with international best practices. The methodology consisted in the creation of a questionnaire reflecting the Greek CG code, which basically replicate the OECD Principles. Other, well-regarded CG codes were taken into account. Then, we constructed a rating system based on CG indicators and we applied it for the years 2001 and 2003. The total rating results for the years 2001 and 2003 demonstrated a relatively satisfactory improvement. The highest compliance is in the category of shareholder rights, while weak compliance appears in the last category, which incorporates commitment to CG, CSR and the relations with shareholders. The exercise, using practically all agreed principles of the OECD, could demonstrate a reasonable degree of compliance of the average company rated. Its limitation in that respect is that it could not satisfy investigations on convergence. The indicators used were highly pertinent to measure compliance, but not convergence, which was not within the initial targets and would need a longer time series analysis. Our methodology applies in a small open economy and may have significant implications in other similar capital markets. Methodologically, the merit of the exercise lies in its approach toward the creation of "collectively subjective" weightings, and is valuable to institutional investors, policymakers, regulators and academics.
Marginal cost pricing of scheduled transport services

A useful general price theory for the whole transport sector is difficult to imagine, in view of the many important differences within the transport sector in both demand and supply. The most common approach is to deal separately with each mode of transport. This is the most natural division from a transport technological point of view. Another division of the transport sector can be more adequate from an economic point of view. Instead of considering the pricing problems of each mode of transport separately, it seems in many respects more appropriate to divide transport price theory into these three departments : Price theory for track (road, rail, fairway) services Price theory for services rendered at passenger and freight handling ' ' terminals". Price theory for services rendered by transport vehicles, or simply "transport services". The third department should, in turn, be divided into the subdepartments of the "charter" market and the market for "scheduled transport services". The present discussion is about marginal cost pricing of scheduled transport services? sts for short.
Industrial Production and Capacity Utilization

Despite the downward revision to IP in 1999 and 2000, the general contour is the same as in the earlier estimates. After having picked up in the second half of 1999 and after having posted rapid gains in the first half of 2000, increases in industrial output abated noticeably at mid-year. According to the revised data, however, industrial output was weaker in the second half of 2000 than in the earlier estimates.
The Wisdom of Teams

The Fundamentals of Teams Managers think they know what teams are. Most understand that their organizations’ need for good teams may be growing in the face of increased change and its challenges. However, often they either don’t know what it takes to make a team function well or they don’t apply what they do know, even when it is accurate. To work well – to truly cohere – a team needs a “demanding performance challenge. ” Teams often come into being to rise to a diffi cult challenge. However, as you form a team, don’t overlook “team basics”: how large the team is, what skills its members have, to whom it reports and what goals it pursues. Performance is key to creating teams. A company with “high performance standards” is likelier to create high-performance teams than a company that simply teaches teamwork. No matter what your company emphasizes, high-performance teams are uncommon. Many people think teams work best in a horizontal structure, but that’s not true. Teams function best when they can depend on their leaders to set clear standards and create dependable, supportive processes. “Understanding Teams” Even though most of your employees probably were raised with a bias for individualistic approaches, you can still build great teams. Your main tool is discipline. To make people accountable, be sure that superior team functioning serves their individual interests. People have to work together repeatedly, in a focused way, to create teams. Teams that develop and take responsibility for performance standards will outperform groups that lack such standards. By building shared standards and communication patterns, teams can speed up your organization’s response to problems, allowing it to react in “real time” rather than waiting “Much of the wisdom of teams lies in the disciplined pursuit of performance. ” “We believe that teams – real teams, not just groups that management calls ‘teams’ – should be the basic unit of performance for most organizations, regardless of size. ”
Density functional investigations of the properties and thermochemistry of UFn and UCln (n=1,...,6).

The structural properties and thermochemistry of the UF(n) and UCl(n) (n=1,.,6) molecules have been investigated using hybrid density functional theory and a small-core (60 electrons) relativistic effective core potential for the uranium atom. For the first time Bond dissociation energies for this whole series are computed and shown to be in good agreement with experiment. The geometry and electronic structure of each molecule was characterized.
Optic cup segmentation from fundus images for glaucoma diagnosis

ABSTRACT Glaucoma is a serious disease that can cause complete, permanent blindness, and its early diagnosis is very difficult. In recent years, computer-aided screening and diagnosis of glaucoma has made considerable progress. The optic cup segmentation from fundus images is an extremely important part for the computer-aided screening and diagnosis of glaucoma. This paper presented an automatic optic cup segmentation method that used both color difference information and vessel bends information from fundus images to determine the optic cup boundary. During the implementation of this algorithm, not only were the locations of the 2 types of information points used, but also the confidences of the information points were evaluated. In this way, the information points with higher confidence levels contributed more to the determination of the final cup boundary. The proposed method was evaluated using a public database for fundus images. The experimental results demonstrated that the cup boundaries obtained by the proposed method were more consistent than existing methods with the results obtained by ophthalmologists.
Direct growth of horizontally aligned carbon nanotubes between electrodes and its application to field-effect transistors

This paper presents direct growth of horizontally aligned carbon nanotubes (CNTs) between two predefined various inter-spacing up to tens of microns of electrodes (pads) and its use as CNT field-effect transistors (CNT-FETs). The catalytic metals were prepared, consisting of iron (Fe), aluminum (Al) and platinum (Pt) triple layers, on the thermal silicon oxide substrate (Pt/Al/Fe/SiO2). Scanning electron microscopy measurements of CNT-FETs from the as-grown samples showed that over 80% of the nanotubes are grown across the catalytic electrodes. Moreover, the number of CNTs across the catalytic electrodes is roughly controllable by adjusting the growth condition. The Al, as the upper layer on Fe electrode, not only plays a role as a barrier to prevent vertical growth but also serves as a porous medium that helps in forming smaller nano-sized Fe particles which would be necessary for lateral growth of CNTs. Back-gate field effect transistors were demonstrated with the laterally aligned CNTs. The on/off ratios in all the measured devices are lower than 100 due to the drain leakage current.
Emticicia sediminis sp. nov. isolated from sediment of a shallow stream.

A novel bacterial strain, designated JBR12T, was isolated from sediment of a shallow stream in Cheonan, Korea. Phylogenetic analysis based on 16S rRNA gene sequences showed that strain JBR12T belongs to the genus Emticicia, and indicated that its closest relatives are Emticicia oligotrophica DSM 17448T (97.8 % sequence similarity) and E. ginsengisoli Gsoil 085T (94.3%). A DNA-DNA hybridization experiment revealed < 70 % genomic relatedness between strain JBR12T and E. oligotrophica DSM 17448T. The major fatty acids (>5% of the total) were iso-C15 : 0, summed feature 3 (C16 : 1ω7c and/or C16 : 1ω6c), iso-C15 : 0 3-OH, anteiso-C15 : 0 and iso-C15 : 0 3-OH. The DNA G+C content of strain JBR12T was 37.7 mol%. According to data from the present polyphasic taxonomic study, strain JBR12T represents a novel species of the genus Emticicia, for which the name Emticicia sediminis sp. nov. is proposed. The type strain is JBR12T ( = KACC 17466T = JCM 19321T).