Miracle-dz/UniFAR-FTUs huggingface dataset:
Breaking the self-averaging properties of spatial galaxy fluctuations in the Sloan Digital Sky Survey – Data release six

Statistical analyses of finite sample distributions usually assume that fluctuations are self-averaging, i.e. statistically similar in different regions of the given sample volume. By using the scale-length method, we test whether this assumption is satisfied in several samples of the Sloan Digital Sky Survey Data Release Six. We find that the probability density function (PDF) of conditional fluctuations, if filtered on large enough spatial scales (i.e., $r>30$ Mpc/h), shows relevant systematic variations in different subvolumes of the survey. Instead for scales of $r K -corrections and standard evolutionary corrections, do not qualitatively change the relevant behaviors. We consider in detail the relation between several statistical measurements generally used to quantify galaxy fluctuations and the scale-length analysis by discussing how the breaking of self-averaging properties makes it impossible to have a reliable estimation of average fluctuations amplitude, variance, and correlations for $r>30$ Mpc/h. Finally we show that the large-amplitude galaxy fluctuations observed in the SDSS samples are at odds with the predictions of the standard Λ CDM model of structure formation.
Sequential versus simultaneous viewing of an environment: Effects of focal attention to individual object locations on visual spatial learning

We investigated memories of room-sized spatial layouts learned by sequentially or simultaneously viewing objects from a stationary position. In three experiments, sequential viewing (one or two objects at a time) yielded subsequent memory performance that was equivalent or superior to simultaneous viewing of all objects, even though sequential viewing lacked direct access to the entire layout. This finding was replicated by replacing sequential viewing with directed viewing in which all objects were presented simultaneously and participants’ attention was externally focused on each object sequentially, indicating that the advantage of sequential viewing over simultaneous viewing may have originated from focal attention to individual object locations. These results suggest that memory representation of object-to-object relations can be constructed efficiently by encoding each object location separately, when those locations are defined within a single spatial reference system. These findings highlight the importance of considering object presentation procedures when studying spatial learning mechanisms.
A User-Oriented, Customizable Infrastructure Sharing Approach for Hybrid Cloud Computing Environments

It is widely accepted that cloud computing technologies will soon have substantial impact on a broad range of industrial and institutional sectors such as governance, health care, education, agriculture, logistics, manufacturing, media etc. Cloud infrastructures are typically based on virtualized environments to allow physical infrastructure to be shared by multiple and diverse end users. However, the efficient sharing of a cloud infrastructure can be performed only through user-centered service admission control procedure, which should also be flexible enough to adapt to the various real market cloud deployment scenarios. Several conflicting parameters such as the type of the hybrid cloud infrastructure being deployed, multiple user priority groups, security, energy efficiency and financial costs should also be taken into account. Thus, aiming to deal with all these emerging resource management trade-off problems, we propose in this paper a user-oriented, highly customizable infrastructure sharing approach, namely IaaS Request Admission Control (IRAC), designed for Hybrid Cloud Computing Environments.
Snf1-Dependent and Snf1-Independent Pathways of Constitutive ADH2 Expression in Saccharomyces cerevisiae

The transcription factor Adr1 directly activates the expression of genes encoding enzymes in numerous pathways that are upregulated after the exhaustion of glucose in the yeast Saccharomyces cerevisiae. ADH2, encoding the alcohol dehydrogenase isozyme required for ethanol oxidation, is a highly glucose-repressed, Adr1-dependent gene. Using a genetic screen we isolated >100 mutants in 12 complementation groups that exhibit ADR1-dependent constitutive ADH2 expression on glucose. Temperature-sensitive alleles are present among the new constitutive mutants, indicating that essential genes play a role in ADH2 repression. Among the genes we cloned is MOT1, encoding a repressor that inhibits TBP binding to the promoter, thus linking glucose repression with TBP access to chromatin. Two genes encoding proteins involved in vacuolar function, FAB1 and VPS35, and CDC10, encoding a nonessential septin, were also uncovered in the search, suggesting that vacuolar function and the cytoskeleton have previously unknown roles in regulating gene expression. Constitutive activation of ADH2 expression by Adr1 is SNF1-dependent in a strain with a defective MOT1 gene, whereas deletion of SNF1 did not affect constitutive ADH2 expression in the mutants affecting vacuolar or septin function. Thus, the mutant search revealed previously unknown Snf1-dependent and -independent pathways of ADH2 expression.
A Three-Pass Establishment Protocol for Real-Time Multiparty Communication

The development of high-speed networks and global internetworking protocols enable new, multimedia-oriented, applications to emerge, such as teleconferencing and other collaborative applications, or video-on-demand. These new applications rely on the underlying communication infrastructure to be able to provide Quality of Service (QoS) guarantees, typically in form of delay and jitter bounds. Appropriate admission control during connection establishment is necessary for the underlying communication infrastructure to satisfy the above QoS requirements. Admission control is used in conjunction with a resource reservation protocol that reserve resources at communication establishment time. Existing resource reservation algorithms are limited when it comes to reserving resources for multiparty communication environments, in particular for multicast connections. We propose a new protocol for connection establishment in a real-time one-to-many communication environment. This algorithm very effectively allocates resources for connections along their multicast routes, and thus reduces call-blocking probabilities and increases resource utilization while providing QoS guarantees. This is illustrated with a suite of simulation experiments, which compares the performance of our approach with that of other existing protocols.
Eurographics Symposium on Point-based Graphics (2006) Interactive Out-of-core Texturing with Point-sampled Textures

The visualization of huge 3D objects becomes available on common workstations thanks to highly optimized data-structures and out-of-core frameworks for rendering. However, the editing, and in particular, the tex-turing of such objects is still a challenging task, since usual methods for optimized rendering are not easily amenable to interactive modification. In this paper, we introduce the idea of point-sampled textures, and show how to interactively texture such a huge model at various scales, without any parameterization. An adaptive in-core point-based approximated geometry is first created by employing an efficient out-of-core point-sampling algorithm. This simplified geometry is then used for an interactive and multi-scale point-based texturing. Finally, a feature-preserving kernel is used to convert the point-based model into a global 3D texture which can be applied back on the initial huge geometry. Our technique thus provides a flexible tool to generate, edit and apply size-independent textures to a wide range of huge 3D objects thanks to point-based methods. Example: Starting from a large (8M polygons here) out-of-core geometry (left), our technique generates an adap-tive in-core point-based approximated geometry (150k samples) that is used for interactive multi-scale texturing (middle). The so-defined " point-sampled texture " is then upscaled with a feature-preserving kernel, and applied on the initial geometry (right).
Long-Term Costs and Health Impact of Continued Global Fund Support for Antiretroviral Therapy

Background By the end of 2011 Global Fund investments will be supporting 3.5 million people on antiretroviral therapy (ART) in 104 low- and middle-income countries. We estimated the cost and health impact of continuing treatment for these patients through 2020. Methods and Findings Survival on first-line and second-line ART regimens is estimated based on annual retention rates reported by national AIDS programs. Costs per patient-year were calculated from country-reported ARV procurement prices, and expenditures on laboratory tests, health care utilization and end-of-life care from in-depth costing studies. Of the 3.5 million ART patients in 2011, 2.3 million will still need treatment in 2020. The annual cost of maintaining ART falls from $1.9 billion in 2011 to $1.7 billion in 2020, as a result of a declining number of surviving patients partially offset by increasing costs as more patients migrate to second-line therapy. The Global Fund is expected to continue being a major contributor to meeting this financial need, alongside other international funders and domestic resources. Costs would be $150 million less in 2020 with an annual 5% decline in first-line ARV prices and $150–370 million less with a 5%–12% annual decline in second-line prices, but $200 million higher in 2020 with phase out of stavudine (d4T), or $200 million higher with increased migration to second-line regimens expected if all countries routinely adopted viral load monitoring. Deaths postponed by ART correspond to 830,000 life-years saved in 2011, increasing to around 2.3 million life-years every year between 2015 and 2020. Conclusions Annual patient-level direct costs of supporting a patient cohort remain fairly stable over 2011–2020, if current antiretroviral prices and delivery costs are maintained. Second-line antiretroviral prices are a major cost driver, underscoring the importance of investing in treatment quality to improve retention on first-line regimens.
Using Subgroup Discovery Metrics to Mine Interesting Subgraphs

While extensive work has been done in both graph mining and subgroup discovery, the potential benefits of combining the two fields have not been well studied. We propose, implement, and evaluate an adaption of an existing subgroup discovery algorithm to mine graph data. Our experiments use two different metrics from the subgroup discovery literature to demonstrate value in using such metrics to guide subgraph discovery and to build a foundation to support further studies combining subgroup discovery and graph mining.
Recommendation Strategies for Promoting eLearning Performance Factors for All

Personalized inclusive eLearning requires a dynamic support in terms of recommendation strategies that combines design time and runtime approaches. This support is to be provided by standard-based open learning management systems. In this paper, we identify different situations during the delivery of a course based on the Collaborative Logical Framework approach and propose when to recommend and what recommendations are to be provided to the learners to improve their performance by addressing eLearning critical factors. Expert evaluations and empirical studies maintain this work.
A new multiobjective evolutionary algorithm: OMOEA

A new algorithm is proposed to solve constrained multiobjective problems. The constraints of the MOPs are taken account of in determining Pareto dominance. As a result, the feasibility of solutions is not an issue. At the same time, it takes advantage of both the orthogonal design method to search evenly, and the statistical optimal method to speed up the computation. The output of the technique is a large set of solutions with high precision and even distribution. Notably, for an engineering problem WATER, it finds the Pareto-optimal set, which was previously unknown.
A New Method for Measuring Text Similarity in Learning Management Systems Using WordNet

As text sources are getting broader, measuring text similarity is becoming more compelling. Automatic text classification, search engines and auto answering systems are samples of applications that rely on text similarity. Learning management systems (LMS) are becoming more important since electronic media is getting more publicly available. As LMS continuously needs content enrichment and the web is getting richer, automatic collection of learning materials becomes an innovative idea. Intelligent agents can be used with a similarity measurement method to implement the automatic collection process. This paper presents a new method for measuring text similarity using the well-known WordNet Ontology. The proposed method assumes that a text is similar to another if it represents a more specific semantic. This is more suitable for LMS content enrichment as learning content can usually be expanded by a more specific one. This paper shows how the hierarchy of WordNet can be taken advantage of to determine the importance of a word. It is also shown how similarity method within an e-learning system is exploited to achieve two goals. The first one is the enrichment of the e-learning content, and the second is the detection of semantically similar questions in e-learning questions banks.
WAVELET ENHANCEMENT OF CLOUD-RELATED SHADOW AREAS IN SINGLE LANDSAT SATELLITE IMAGERY

: Cloud-related shadows represent areas with low illumination conditions that affect remote sensing image quality. In this research, a wavelet-based image sharpening algorithm was developed to enhance shadow areas independently using the defected cloudy image information. The developed algorithm is applied locally by boosting the image high frequency content in the shadow areas using the defected image de-noised wavelet coefficients. Image entropy was used as a measure to determine the change in wavelet coefficient values. The developed algorithm was tested on the panchromatic band of a November 2001 Landsat 7 ETM satellite subscenes. Another cloud-free image was used as reference image for results evaluation and quality analysis. Several discrete wavelet decomposition levels were tested. Quantitative measures were used to evaluate the obtained results. Visual and quantitative analysis of the results revealed that the ability to enhance details under shadow areas increased with the increase in the number of wavelet decomposition levels. Two or three wavelet decomposition levels were found to be sufficient for enhancing image quality in the shadow areas while avoiding introduced artifacts. Conclusions and recommendations are given with respect to the suitability, accuracy and efficiency of this method.
Schedulability analysis for Fault tolerance real-time system under fault bursts

Burst error model describes phenomena which cause potentially random faults over a bounded time interval. We study the worst response time for tasks under fixed-priority with checkpoints. Since checkpointing schemes depend on time redundancy, they could affect the correctness of the system by causing deadlines to be missed. In this paper, we provide an exact schedulability analysis for burst error model and derive the optimal number of checkpoints. We also explore the fault-tolerant priority assignment policy to get the most efficient scheme.
Development of Enhanced Active Shape Model (EASM) for in-situ Automatic Optical Inspection (AOI)

Conventional current active shape model (ASM) applied to in-situ Automatic Optical Inspection (AOI) has the drawback of inability to locate position, size or orientation of detected targets. This article presents an enhanced active shape model (EASM), which evaluates both offset and orientation during component detection and positioning. The developed method is employed to inspect various electronic components mounted on printed circuit boards (PCB). Experimental results show that it can achieve both robustness and accuracy. In addition, the accuracy of component positioning increases with increasing number of sample images used for building the model, and peaks at the threshold number of images, which varies with quality of the EASM in representing the detected component. Our findings validate the feasibility of applying the developed approach to production environment.
The Investigation of Student Dropout Prediction Model in Thai Higher Education Using Educational Data Mining: A Case Study of Faculty of Science, Prince of Songkla Uni-versity

The student’s retention rate is one of the challenging issues that representing the quality of the university. A high dropout rate of students affects not only the reputation of the university but also the students’ career in the future. Therefore, there is a need of student dropout analysis in order to improve the academic plan and management to reduce students drop out from the university as well as to enhance the quality of the higher education system. Data mining technique provides powerful methods for analysis and the prediction the dropout. This paper proposes a model for predicting students’ dropout using the dataset from the representative of the largest public university in the Southen part of Thailand. In this study, data from Faculty of Science, Prince of Songkla University was collected from academic year of 2013 to 2017. The experiment result shows that JRip rule induction is the best technique to generate a prediction model receiving the highest accuracy value of 77.30%. The results highlight the potential prediction model that can be used to detect the early state of dropping out of the student which the university can provide supporting program to improve the student retention rate
Valuation of financial models with non-linear state spaces

A common assumption in valuation models for derivative securities is that the underlying state variables take values in a linear state space. We discuss numerical implementation issues in an interest rate model with a simple non-linear state space, formulating and comparing Monte Carlo, finite difference and lattice numerical solution methods. We conclude that, at least in low dimensional spaces, non-linear interest rate models may be viable.
Generalised Soundness of Work ow Nets is

We investigate the decidability of the problem of generalised soundness for Work ow nets: \Every marking reachable from an initial marking with k tokens on the initial place terminates properly, i.e. it can reach a marking with k tokens on the nal place, for an arbitrary natural number k". We start with considering simple correctness criteria for Work ow nets and reduce them to the check of structural properties formulated in terms of traps and siphons, which can be easily checked. We call the nets that possess those properties Batch Work ow nets (BWF-nets). We show that every WF-net is either not sound or it can be transformed to a BWF-net with the same behaviour. Then we use algebraic methods to prove that generalized soundness is decidable for BWF-nets and give a decision procedure.
Clinical Ophthalmology Dovepress

hereby accept the Terms. Non-commercial uses of the work are permitted without any further permission from Dove Medical Press Limited, provided the work is properly attributed. For permission for commercial use of this work, please see paragraphs 4.2 and 5 of our Terms Normal flora of conjunctiva and lid margin, as well as its antibiotic sensitivity, in patients undergoing cataract surgery at Phramongkutklao hospital ravee ratnumnoi narumon Keorochana Chavalit sontisombat Objective: This study aimed to evaluate the normal flora of conjunctiva and lid margin, as well as its antibiotic sensitivity. Design: This was a prospective cross-sectional study. Patients and methods: A prospective study was conducted on 120 patients who underwent cataract surgery at the Phramongkutklao Hospital from September 2014 to October 2014. Conjunctival and lid margin swabs were obtained from patients before they underwent cataract surgery. These swabs were used to inoculate blood agar and chocolate agar plates for culturing. After growth of the normal flora, the antibiotic sensitivity method using tobramycin, moxifloxacin, levofloxacin, and cefazolin was applied. Main outcome measures: Normal flora of conjunctiva and lid margin, along with its antibiotic sensitivity, from patients who underwent cataract surgery was assessed. Results: A total of 120 eyes were included in this study, and bacterial isolation rates were identified. Five bacteria from the lid margin were cultured, namely, coagulase-negative staphylococcus and Staphylococcus aureus (0.83%). Two bacteria from the conjunctiva were cultured, namely, coagulase-negative staphylococcus (30%) and Streptococcus spp. (0.83%). Results of antibiotic sensitivity test showed that all isolated bacteria are sensitive to cefazolin 100%, tobramycin 98.67%, levofloxacin 100%, and moxifloxacin 100%. Conclusion: Coagulase-negative staphylococci are the most common bacteria isolated from conjunctiva and lid margin.
Thermodynamics of (3+1)-dimensional black holes with toroidal or higher genus horizons

We examine counterparts of the Reissner-Nordstr\"om\char21{}anti\char21{}de Sitter black hole spacetimes in which the two-sphere has been replaced by a surface \ensuremath{\Sigma} of constant negative or zero curvature. When horizons exist, the spacetimes are black holes with an asymptotically locally anti\char21{}de Sitter infinity, but the infinity topology differs from that in the asymptotically Minkowski case, and the horizon topology is not ${S}^{2}. $ Maximal analytic extensions of the solutions are given. The local Hawking temperature is found. When \ensuremath{\Sigma} is closed, we derive the first law of thermodynamics using a Brown-York-type quasilocal energy at a finite boundary, and we identify the entropy as one-quarter of the horizon area, independent of the horizon topology. The heat capacities with constant charge and constant electrostatic potential are shown to be positive definite. With the boundary pushed to infinity, we consider thermodynamical ensembles that fix the renormalized temperature and either the charge or the electrostatic potential at infinity. Both ensembles turn out to be thermodynamically stable, and dominated by a unique classical solution.
Comparison of medical abortion with surgical vacuum aspiration: women's preferences and acceptability of treatment.

OBJECTIVES--To assess women's preferences for, and the acceptability of, medical abortion and vacuum aspiration in the early first trimester. DESIGN--Patient centred, partially randomised trial. Medical abortion was performed with mifepristone 600 mg followed 48 hours later by gemeprost 1 mg vaginal pessary. Vacuum aspiration was performed under general anaesthesia. SETTING--Teaching hospital in Scotland. PATIENTS--363 women undergoing legal induced abortion at less than nine weeks' gestation. MAIN OUTCOME MEASURES--Women's preferences for method of abortion before abortion; acceptability judged two weeks after abortion by recording the method women would opt to undergo in future and by semantic differential rating technique. RESULTS--73 (20%) women preferred to undergo medical abortion, and 95 (26%) vacuum aspiration; 195 (54%) were willing to undergo either method, and were allocated at random. Both procedures were highly acceptable to women with preferences. Gestation had a definite effect on acceptability in randomised women; at less than 50 days there were no differences, but between 50 and 63 days vacuum aspiration was significantly more acceptable. CONCLUSIONS--Women who wish to use a particular method should be allowed their choice, regardless of gestation. Women of 50-63 days' gestation without preferences for a particular method are likely to find vacuum aspiration more acceptable. A patient centred, partially randomised trial design may be a useful tool in pragmatic research.