Miracle-dz/UniFAR-FTUs huggingface dataset:
Visualization of endogenous p53-mediated transcription in vivo using sodium iodide symporter.

PURPOSE To develop a gamma camera imaging method for the determination of endogenous gene expression, we evaluated the expression of endogenous p53 gene using human sodium iodide symporter (hNIS) gene as reporter. EXPERIMENTAL DESIGN We constructed cis-p53RE-hNIS reporter vector placed under control of an artificial enhancer (p53RE). Moreover, we transfected it into human hepatoma cell line SK-Hep1 by liposome. Geneticin was used for the selection of stable transfectant (SK-Hep1p53NIS). To evaluate the function of hNIS, the inhibition study was examined with 1 mmol/L potassium perchlorate. After treatment of Adriamycin with serial dose for 24 hours, we measured the uptake of 125I and did Western blot analysis to evaluate expression of p53 protein. Tumor xenografts were produced in nude mice by s.c. injection of SK-Hep1p53NIS cells. After 7 days, scintigraphic images of nude mice before and after Adriamycin treatment were obtained using [99mTc]-pertechnetate. RESULTS In the SK-Hep1p53NIS cells, Adriamycin-treated cells accumulated up to three times higher than did nontreated cells. Potassium perchlorate inhibited completely the uptake of 125I. As Adriamycin dose increased, radioiodide uptake was significantly correlated with activated p53 as well as total p53 protein level. When Adriamycin (2 mg/kg) was treated in the same mice, a significantly higher uptake of [99mTc]-pertechnetate was observed in SK-Hep1p53NIS xenografts compared with nontreated xenografts (P < 0.05, unpaired t test). CONCLUSIONS These results suggest that p53 expression level can be monitored by NIS gene expression using cis-p53RE-hNIS system in vitro and in vivo.
Research on optimal planning method of USV for complex obstacles

In this thesis, based on the selected intelligent optimization algorithm - ant colony algorithm, introduced its system and its typical applications are analyzed through operational focus and discussion method algorithm. The main structure of the paper can be divided into two parts: the typical obstacles modeling and the use of global path planning ant colony algorithm. In part modeling, the use of the grid method view and draw use MATLAB model for global planning. In the global planning, the use of MATLAB simulation of the optimal path planning of USV facing typical obstacles, to achieve the desired objectives.
GENETIC ALGORITHM BASED EQUIPMENT SELECTION METHOD FOR CONSTRUCTION PROJECT USING MATLAB TOOL

Equipment selection is a key factor in modern construction industry. As it is a complex factor, current models offered by literatures fail to provide adequate solutions for major issues like systematic evaluation of soft factors and weighting of soft benefits in comparison with costs. This paper aims at making a comparative study between GA and AHP by utilising MATLAB as a tool. It is a convenient tool offering an orderly methodical thinking. It guides them in making consistent decisions and provides a facility for all necessary computation.
Knowledge-based nonuniform crossover

One-point, two-point and k-point crossover can be viewed as special cases of uniform crossover, where genetic material is chosen each locus of either parent with equal probability (G. Syswerda, 1989). The paper generalizes uniform crossover to "non-uniform crossover" using "mask" vectors whose elements are real numbers /spl isin/[0, 1], representing problem-specific knowledge that improves performance by biasing the selection of alleles from either parent. This knowledge based non-uniform crossover (KNUX) is applied to two NP optimization problems: graph partitioning and soft-decision decoding of linear block codes (H.S. Maini, 1993). Simulation results show orders of magnitude improvement of this operator over two-point and uniform crossover. An appropriate schema theorem is also developed. <<ETX>>
Dual Representation of the Semantic User Profile for Personalized Web Search in an Evolving Domain

Several semantic based user profile approaches have been introduced in the literature to learn the users’ interests for personalized search. However, many of them are ill-suited to cope with a domain of information that evolves and user interests that may change over time. In this paper, we propose a novel dual representation of a user’s semantic profile to deal with this problem: (1) a lower-level semantic representation, consisting of an accumulated gathering of user activities over a long period of time, that uses a standard machine learning algorithm to detect user convergence, (2) a higher-level semantic representation that detects shifts in the user activitiesonce this shift is detected, the higher-level semantic representation automatically updates the user profiles and reinitialize the system. Our experimental results demonstrate the feasibility of this approach.
Cost optimization in ASIC implementation of periodic hard-real time systems using behavioral synthesis techniques

Modern applications are often defined as sets of several computational tasks. This paper presents a synthesis algorithm for ASIC implementations which realize multiple computational tasks under hard real-time deadlines. The algorithm analyzes constraints imposed by task sharing as well as the traditional datapath synthesis criteria. In particular we demonstrated an efficient technique to combine rate-monotonic scheduling, a widely used hard real-time systems scheduling discipline, with estimations and scheduling and allocation algorithms. Matching the number of bits in tasks assigned to the same processor was the most important factor in obtaining good designs. We have demonstrated the effectiveness of our algorithms on several multiple-task examples.
Speech recognition using voice-characteristic-dependent acoustic models

This paper proposes a speech recognition technique based on acoustic models considering voice characteristic variations. Context-dependent acoustic models, which are typically triphone HMM, are often used in continuous speech recognition systems. This work hypothesizes that the speaker voice characteristics that humans can perceive by listening are also factors in acoustic variation for construction of acoustic models, and a tree-based clustering technique is also applied to speaker voice characteristics to construct voice-characteristic-dependent acoustic models. In speech recognition using triphone models, the neighboring phonetic context is given from the linguistic-phonetic knowledge in advance; in contrast, the voice characteristics of input speech are unknown in recognition using voice-characteristic-dependent acoustic models. This paper proposes a method of recognizing speech even under conditions where the voice characteristics of the input speech are unknown. The result of a gender-dependent speech recognition experiment shows that the proposed method achieves higher recognition performance in comparison to conventional methods.
Research on hotel staff job satisfaction: The case of Shanghai

Based on a job satisfaction survey to nearly 400 in-service hotel staff in Shanghai, this research uses factor analysis to explore the latent factors that might affect the job satisfaction of Shanghai hotel staff and uses one-way ANOVA to examine the significance of each factor to Shanghai hotel staff job satisfaction. This research will be helpful to discover the various demands of Shanghai hotel staff, give supports to Shanghai hotel managers, and also provide a better way to understand the Chinese hospitality industry.
A REVIEW OF CLUSTER BASED CLASSIFICATION TECHNIQUE

Fusion and ensemble is important technique of machine learning. Fusion fused the feature attribute of different classifier and improved the classification of binary classifier. Instead of that ensemble technique provide the facility of merge two individual classifier and improve the performance of both classifiers. The ensemble technique of classifier depends on number of nearer point of classifier. For the selection of nearest point of classifier various authors used clustering technique for ensemble process. The cluster based ensemble technique suffered a problem of optimal selection of cluster during ensemble process. The generation of clustering technique is fixed due to this reasons the selection of optimal cluster is very difficult. In this paper gives the information about ensemble technique based on clustering and other technique.
Personalization in crowd-driven annotation for cultural heritage collections

Many cultural heritage institutions are confronted with a big challenge when it comes to adapting the process of registration, annotation and digitization of their collections to meet the new technological demands for providing their collections online with Web and mobile technologies. With limited funding and limited professional resources, annotation is often lagging behind significantly in terms of quantity and level of detail. Quantity as well as quality of the annotations is the key to finding relevant objects by various groups of users in online collections. As many experiments with cultural heritage data online show, human computation can be useful for collecting large quantities of data. Various of these experimented with a crowd of lay people to help with the annotation of cultural heritage artefacts. However, a common concern relates to the resulting quality. The current trend appears to focus on supporting ‘the crowd’ to achieve the desired level of quality. In this paper, we discuss the results of the first phase of an evolutionary system design performed in collaboration with the Rijksmuseum Amsterdam, as part of the SEALINCMedia project. By providing personalized support to the individuals and groups in the ‘crowd’ when annotating museum collection objects, we also support the integration of the annotation result in the RMA content management system. The contribution of this paper is twofold: (1) requirements specification for a crowdsourcing annotation process and (2) design of the personalization functionality in a crowdsourcing annotation system.
Extending the SkelCL Skeleton Library for Stencil Computations on Multi-GPU Systems

The implementation of stencil computations on modern, massively parallel systems with GPUs and other accelerators currently relies on manually-tuned coding using low-level approaches like OpenCL and CUDA, which makes it a complex, time-consuming, and error-prone task. We describe how stencil computations can be programmed in our SkelCL approach that combines high level of programming abstraction with competitive performance on multi-GPU systems. SkelCL extends the OpenCL standard by three high-level features: 1) pre-implemented parallel patterns (a.k.a. skeletons); 2) container data types for vectors and matrices; 3) automatic data (re)distribution mechanism. We introduce two new SkelCL skeletons which specifically target stencil computations – MapOverlap and Stencil – and we describe their use for particular application examples, discuss their efficient parallel implementation, and report experimental results on manycore systems with multiple GPUs.
CAOS: a collaborative and open spatial structure service component with incremental spatial parsing

This paper introduces a project that provides spatial hypermedia services as part of a component-based open hypermedia system (CB-OHS). We focus on the issues of storing both the information space and the parsed spatial structure (for structure sharing purposes) and collaboration support. Continuous re-parsing of spatial structure guarantees consistency between spatial and parsed structure. This promotes parsed structure to first-class status, making persistent storage of it attractive; and, it ensures a consistent view of the parsed structure between collaborative users. For efficiency reasons, the spatial parser is incremental. An accompanying spatial editor shows the validity and utility of the approach.
The concept of surrogacy in Nigeria: Issues, prospects and challenges

The journey from girlhood to womanhood in Africa begins with betrothal to marriage. This journey is not complete and the place of an African woman is not secure in her matrimonial home until such time as she is able to procreate. As such, reproduction is an essential aspect of the African family system. The inability of an African woman to fall pregnant within months of marriage is usually seen as a cause for anxiety and if this condition continues for some years, the woman is tagged barren and treated as a woman with a disability, seeing that the inability to conceive is seen as such. In most cases the husband’s family mount pressure on the husband to either marry an additional wife or another wife in order to produce a child. This leads many women to make desperate decisions which may not necessarily be legally recognised, including the practice of buying babies. The article examines the legal framework for surrogacy in Nigeria. It adopts a comparative method and compares the legal frameworks governing surrogacy in Nigeria and South Africa. It concludes that there is a lacuna regarding surrogacy in the laws of Nigeria which allows for abuse during the surrogacy, and makes policy recommendations to provide the legal architecture to protect stakeholders in surrogate agreements in Nigeria.
A HYBRID FILTERING APPROACH TO RETINAL VESSEL SEGMENTATION

We propose a novel vessel enhancement filter for retinal images. The filter can be used as a preprocessing step in applications such as vessel segmentation/visualization, and pathology detection. The proposed filter combines the eigenvalues of the Hessian matrix, the response of matched filters, and edge constraints on multiple scales. The eigenvectors of the Hessian matrix provide the orientation of vessels and so only one matched filter is necessary at each pixel in a given scale. This makes the proposed filter more efficient compared with existing multiscale matched filters. Edge constraints are used to suppress the response of spurious boundary edges. Experimental evaluation on the publicly available DRIVE dataset demonstrate improved performance of the proposed filter compared with known techniques.
Predict the success or failure of an evolutionary algorithm run

The quality of candidate solutions in evolutionary computation (EC) depend on multiple independent runs and a large number of them fail to guarantee optimal result. These runs consume more or less equal or sometimes higher amount of computational resources on par the runs that produce desirable results. This research work addresses these two issues (run quality, execution time), Run Prediction Model (RPM), in which undesirable quality evolutionary runs are identified to discontinue from their execution. An Ant Colony Optimization (ACO) based classifier that learns to discover a prediction model from the early generations of an EC run. We consider Grammatical Evolution (GE) as our EC technique to apply RPM that is evaluated on four symbolic regression problems. We establish that the RPM applied GE produces a significant improvement in the success rate while reducing the execution time.
The mass ratio distribution of B-type visual binaries in the Sco OB2 association

A sample of 115 B-type stars in the Sco OB2 association is examined for existence of visual companions in the J and K s bands, using the ADONIS near-infrared adaptive optics system and coronograph. Practically all the components in the separation range $0\farcs3$–$6\farcs4$ (45–900 AU) and magnitudes down to $K\! =\! 16$ were detected. The K and $J\! -\! K$ photometry of the primaries and differential photometry and astrometry of the 96 secondaries are presented. Ten secondaries are new physical components, as inferred from the photometric and statistical criteria, while the rest of the newly detected objects are faint background stars. After a small correction for detection incompleteness and a conversion of the fluxes into masses, an unbiased distribution of the components mass ratio q was derived. The power law $f(q)\propto q^{-0.5}$ fits the observations well, whereas a q -1.8 distribution, which corresponds to a random pairing of stars, is rejected. The companion star fraction is $0.20\pm0.04$ per decade of separation which is comparable to the highest measured binary fraction among low-mass PMS stars and ~1.6 times higher than the binary fraction of low-mass dwarfs in the solar neighborhood and in open clusters in the same separation range.
A moving planar mirror based approach for cultural reconstruction

Modelling from images is a cost‐effective means of obtaining virtual cultural heritage models. These models can be effectively constructed from classical Structure from Motion algorithm. However, it's too difficult to reconstruct whole scenes using SFM method since general oriental historic sites contain a very complex shapes and brilliant colours. To overcome this difficulty, the current paper proposes a new reconstruction method based on a moving planar mirror. We devise the mirror posture instead of scene itself as a cue for reconstructing the geometry. That implies that the geometric cues are inserted into the scene by compulsion. With this method, we can obtain the geometrical details regardless of the scene complexity. For this purpose, we first capture image sequences through the moving mirror containing the interested scene, and then calibrate the camera through the mirror's posture. Since the calibration results are still inaccurate due to the detection error, the camera pose is revised using frame‐correspondence of the corner points that are easily obtained using the initial camera posture. Finally, 3D information is computed from a set of calibrated image sequences. We validate our approach with a set of experiments on some cultural heritage objects. Copyright © 2004 John Wiley & Sons, Ltd.
Recreational Tourism: Demands and Impacts

Preface 1. A History of Tourism in the English Speaking World 2. The Economic Determinants of Demand 3. The Social Determinants of Demand 4. The Psychological Determinations of Demand 5. The Tourism Experience 6. The Tourist Resort Zone 7. The Economic Impacts of Tourism 8. Tourism Impacts on the Environment 9. The Social Impacts of Tourism 10. Concluding Words
Oculomotor Control and the Maintenance of Spatially and Temporally Distributed Events in Visuo-Spatial Working Memory

Previous studies have demonstrated that working memory for spatial location can be significantly disrupted by concurrent eye or limb movement (Baddeley, 1986; Smyth, Pearson, & Pendleton, 1988). Shifts in attention alone can also interfere with spatial span (Smyth & Scholey, 1994), even with no corresponding movement of the eyes or limbs (Smyth, 1996). What is not clear from these studies is how comparable is the magnitude of effect caused by different forms of spatial disrupter. Recently, it has been demonstrated that limb movements produce as much interference with spatial span as do reflexive saccades (Lawrence, Myerson, Oonk, & Abrams, 2001). In turn this has led to the hypothesis that all spatially directed movement can produce similar effects in visuo-spatial working memory. This paper reports the results of five experiments that have contrasted the effect of concurrent eye movement, limb movement, and covert attention shifts on participants’ working memory for sequences of locations. All conditions involving concurrent eye movement produced significantly greater reduction in span than equivalent limb movement or covert attention shifts with eyes fixated. It is argued that these results demonstrate a crucial role for oculomotor control processes during the rehearsal of location-specific representations in working memory.
How To Make Strategic Alliances Work

New research shows that among today's numerous strategic alliances, the most successful are in companies with a department specifically assigned to overseeing alliances. Management professors Jeffrey H. Dyer, Prashant Kale and Harbir Singh came to that conclusion after conducting an in-depth study of 200 corporations and their 1,572 alliances. The number of strategic alliances has increased dramatically over the past decade, with more than 20,000 reported during the last two years alone. On average, the top 500 global companies each participate in 60 major strategic alliances. Fraught with risk, almost half fail. The authors set out to discover why some companies manage alliances effectively when others fail. They found that organizations such as Hewlett-Packard, Oracle, Eli Lilly & Co. and Parke Davis, which excel at generating value from alliances, have a dedicated strategic-alliance function. Companies with a dedicated function were better at solving problems related to the four key alliance-management elements ? knowledge management, external visibility, internal coordination and accountability. A dedicated function, the authors show, acts as a focal point for learning and for leveraging feedback from prior and ongoing alliances. It systematically establishes processes to articulate, document, codify and share alliance know-how. The authors found that one benefit of creating an alliance function was that it compelled companies to create metrics for evaluating the performance of all their alliances. And regular evaluations alerted senior managers to intervene when a particular alliance was struggling. Many companies with dedicated alliance functions report codifying alliance-management knowledge. They create guidelines to help with specific aspects of the alliance life cycle, such as partner selection or alliance negotiation. Some companies establish training programs, both formal ones and informal ones ? such as roundtables that let managers of various alliances share their experience. When done properly, dedicated alliance functions offer internal legitimacy to alliances, assist in setting strategic priorities and draw on resources across the company. That is why, the authors advise, the function cannot be buried within a particular division or be relegated to low-level support within business development.
A polynomial fractional-order charge-controlled memristor model

In this paper, the fractional calculus is introduced into charge-controlled memristor to establish a fractional-order charge-controlled memristor model. The fractional derivative is a generalization of integer derivatives. Memristor represents the missing relation between the charge and flux among the conventional elements. A unified cubic model is proposed which is more general and comprehensive, and the model is analyzed when the fractional-order a change in the range of 0 to 1.0. Some integer-order memristor model simulation are given to have a better understanding for the fractional-order model. Some interesting phenomena are found when researching the fractional-order model that the V-I characteristic is not the conventional double-loop V-I curves, but an curve can be called triple-loop V-I curves. The area inside the hysteresis loops decreases by the increasing of input frequency and the decreasing of the fractional-order α.
The Application of HLLC Numerical Solver to the Reduced Multiphase Model

The performance of high-resolution schemes is investigated for unsteady, inviscid and compressible multiphase flows. An Eulerian diffuse interface approach has been chosen for the simulation of multicomponent flow problems. The reduced fiveequation and seven equation models are used with HLL and HLLC approximation. The authors demonstrated the advantages and disadvantages of both seven equations and five equations models studying their performance with HLL and HLLC algorithms on simple test case. The seven equation model is based on two pressure, two velocity concept of Baer–Nunziato [10], while five equation model is based on the mixture velocity and pressure. The numerical evaluations of two variants of Riemann solvers have been conducted for the classical one-dimensional air-water shock tube and compared with analytical solution for error analysis. Keywords—Multiphase flow, gas-liquid flow, Godunov schems, Riemann solvers, HLL scheme, HLLC scheme.