Miracle-dz/UniFAR-FTUs huggingface dataset:
The reaserch on parameters of spectral clustering based on SVD

The spectral clustering algorithm, which cluster by using the eigenvalues and eigenvectors of Laplacian matrix, may not be obtained the desired clustering results in some cases. It is possible to remedy this deficiency by using the singular value decomposition (SVD) in the spectral clustering algorithm. It is presented in this article the algorithm of spectral clustering based on SVD which use singular value decomposition (SVD) instead of Laplacian eigenmaps. The choice of singular vectors, the estimate of the Gaussian kernel parameter, and the determine of the clusters number significantly influence the clustering results. The experiments show that these spectral clustering parameters such as the number of clusters, etc. can be calculated by use of the dimensionality reduction factor and the expression of singular value.
Oral Administration of Cilostazol Increases Ocular Blood Flow in Patients with Diabetic Retinopathy

Purpose To investigate the effect of cilostazol on ocular hemodynamics and to determine whether the administration of cilostazol increases the ocular blood flow in patients with diabetic retinopathy. Methods This prospective observational study investigated the effect of orally administered cilostazol on diabetic retinopathy. Before and after administration for 1 week, pulsatile ocular blood flow (POBF) and retrobulbar hemodynamics were measured using a POBF analyzer and transcranial Doppler imaging, respectively. Visual acuity, intraocular pressure, and blood pressure were also evaluated before and after treatment. Results Twenty-five eyes of 25 patients were included in this study. POBF increased significantly (16.8 ± 4.6 µL/sec vs. 19.6 ± 6.2 µL/sec, p < 0.001) after administration of cilostazol, while no significant change was identified in visual acuity, intraocular pressure, and blood pressure. Mean flow velocity in the ophthalmic artery as measured with transcranial Doppler imaging also increased significantly after medication (23.5 ± 5.6 cm/sec vs. 26.0 ± 6.9 cm/sec, p = 0.001). The change in POBF directly correlated with the change in mean flow velocity (r = 0.419, p = 0.007). Conclusions Cilostazol was effective in increasing ocular blood flow in patients with diabetic retinopathy, possibly by modulating retrobulbar circulation.
BACK TO NATURE OR NURTURE: USING COMPUTER MODELS IN CREOLE GENESIS Key words: Language acquisition, Creole Genesis, Computational Models

“Artificial societies” are constructed to examine L2-based creole development. ‘Virtual’ slaves and slave-owners interact based on socio-historical conditions. Linguistic transmissions and developments are tracked. This study takes no position on whether a theory of ‘imperfect L2 acquisition of the superstrate language’ can be viewed as final truth with respect to creole genesis. However, a Complex Adaptive System approach sheds light on underlying dynamics of the canonical plantation which produce large-scale effects. Our findings suggest that patterns of adult L2 acquisition presumed under standard L2 creole accounts are not sufficient to explain the emergence of these creoles. Adults in our model created an incipient African-based pidgin which continued with each generation of L2 speakers. Notably, in a previous study we found that ‘prototypical creole’ structures emerged when a very small percentage of older bilingual children were present in the population.
Classification of Induction Machine Faults by Optimal Time–Frequency Representations

This paper presents a new diagnosis method of induction motor faults based on time-frequency classification of the current waveforms. This method is based on a representation space, a selection criterion, and a decision criterion. In order to define the representation space, an optimized time-frequency representation (TFR) is designed from the time-frequency ambiguity plane. The selection criterion is based on Fisher's discriminant ratio, which allows one to maximize the separability between classes representing different faults. A distinct TFR is designed for each class. The following two classifiers were used for decision criteria: the Mahalanobis distance and the hidden Markov model. The flexibility of this method allows an accurate classification independent from the level of load. This method is validated on a 5.5-kW induction motor test bench.
OBSERVATIONS OF THE NEAR-INFRARED SPECTRUM OF THE ZODIACAL LIGHT WITH CIBER

Interplanetary dust (IPD) scatters solar radiation which results in the zodiacal light that dominates the celestial diffuse brightness at optical and near-infrared wavelengths. Both asteroid collisions and cometary ejections produce the IPD, but the relative contribution from these two sources is still unknown. The low resolution spectrometer (LRS) onboard the Cosmic Infrared Background ExpeRiment (CIBER) observed the astrophysical sky spectrum between 0.75 and 2.1 μm over a wide range of ecliptic latitude. The resulting zodiacal light spectrum is redder than the solar spectrum, and shows a broad absorption feature, previously unreported, at approximately 0.9 μm, suggesting the existence of silicates in the IPD material. The spectral shape of the zodiacal light is isotropic at all ecliptic latitudes within the measurement error. The zodiacal light spectrum, including the extended wavelength range to 2.5 μm using Infrared Telescope in Space (IRTS) data, is qualitatively similar to the reflectance of S-type asteroids. This result can be explained by the proximity of S-type asteroidal dust to Earth's orbit, and the relatively high albedo of asteroidal dust compared with cometary dust.
USAdisease in the US adult population

Objective: We investigated the association between glycemic control of type 2 diabetes mellitus (type 2 DM) and severe periodontal disease in the US adult population ages 45years and older. Methods: Data on 4343 persons ages 45– 90years from the National Health and Nutrition Examination Study III were analyzed using weighted multivariable logistic regression. Severe periodontal disease was defined as 2π sites with 6πmm loss of attachment and at least one site with probing pocket depth of 5πmm. Individuals with fasting plasma
Development of Neuro Controller for Negative Output Self-Lift Luo Converter

The present work deals with the application of neuro control theory for the closed loop operation of negative output self-lift Luo converter, which is a newly developed DC-DC converter. Due to the time-varying and switching nature of the power electronic converters, their dynamic behavior becomes highly non-linear. Conventional controllers are incapable of providing good dynamic performance and hence neural network can be utilized as a feedforward controller for controlling power electronic converters. The neuro controller presented in this work is off-line trained using quasi-Newton backpropagation algorithm. The performances of the chosen Luo converter with neuro control are evaluated in this paper (using MATLAB coding) under load and line disturbances. The simulation results are presented. They validate the neuro control developed
Symbolic Arrays in Symbolic PathFinder

Symbolic Execution is a program analysis technique used to increase software reliability. Modern software often manipulate complex data structures, many of which being similar to arrays. We present a novel approach and implementation in Symbolic PathFinder for handling symbolic arrays in Java. It enables analyzing a broader class of programs that manipulates arrays. We also extend the Symbolic Pathfinder testcase generation to support numeric arrays.
Effects of marine actinomycete on the removal of a toxicity alga Phaeocystis globose in eutrophication waters

Phaeocystis globosa blooms in eutrophication waters can cause severely damage in marine ecosystem and consequently influence human activities. This study investigated the effect and role of an algicidal actinomycete (Streptomyces sp. JS01) on the elimination process of P. globosa. JS01 supernatant could alter algal cell membrane permeability in 4 h when analyzed with flow cytometry. Reactive oxygen species (ROS) levels were 7.2 times higher than that at 0 h following exposure to JS01 supernatant for 8 h, which indicated that algal cells suffered from oxidative damage. The Fv/Fm value which could reflect photosystem II (PS II) electron flow status also decreased. Real-time PCR showed that the expression of the photosynthesis related genes psbA and rbcS were suppressed by JS01 supernatant, which might induce damage to PS II. Our results demonstrated that JS01 supernatant can change algal membrane permeability in a short time and then affect photosynthesis process, which might block the PS II electron transport chain to produce excessive ROS. This experiment demonstrated that Streptomyces sp. JS01 could eliminate harmful algae in marine waters efficiently and may be function as a harmful algal bloom controller material.
Enzyme vs. non-enzyme classification based on principal component analysis and AdaBoost classifier

Classifying Enzymes and Non-Enzymes sequences are important and it saves efforts and time. In this paper, machine learning model is proposed to classify the unknown sequences into Enzymes or Non-Enzymes. The proposed model extracts the features from all sequences using the online tool Pepstate from repository “SWISS-PORT” database. Due to high dimensionality, Principal Component Analysis (PCA) technique is used to reduce the dimension of the extracted features. AdaBoost classifier is then used to match the features of unknown sequence with the features of training or labelled sequences. The number of the eigenvectors and the size of the AdaBoost ensemble are investigated to show the influence of each on the accuracy and the CPU time of the proposed model. The proposed model achieved promising results compared with many state-of-the-art methods.
Key mutations stabilize antigen-binding conformation during affinity maturation of a broadly neutralizing influenza antibody lineage

Affinity maturation, the process in which somatic hypermutation and positive selection generate antibodies with increasing affinity for an antigen, is pivotal in acquired humoral immunity. We have studied the mechanism of affinity gain in a human B‐cell lineage in which two main maturation pathways, diverging from a common ancestor, lead to three mature antibodies that neutralize a broad range of H1 influenza viruses. Previous work showed that increased affinity in the mature antibodies derives primarily from stabilization of the CDR H3 loop in the antigen‐binding conformation. We have now used molecular dynamics simulations and existing crystal structures to identify potentially key maturation mutations, and we have characterized their effects on the CDR H3 loop and on antigen binding using further simulations and experimental affinity measurements, respectively. In the two maturation pathways, different contacts between light and heavy chains stabilize the CDR H3 loop. As few as two single‐site mutations in each pathway can confer substantial loop stability, but none of them confers experimentally detectable stability on its own. Our results support models of the germinal center reaction in which two or more mutations can occur without concomitant selection and show how divergent pathways have yielded functionally equivalent antibodies. Proteins 2014; 83:771–780. © 2014 The Authors. Proteins: Structure, Function, and Bioinformatics Published by Wiley Periodicals, Inc.
Probabilistic Association Rules for Item-Based Recommender Systems

Since the beginning of the 1990's, the Internet has constantly grown, proposing more and more services and sources of information. The challenge is no longer to provide users with data, but to improve the human/computer interactions in information systems by suggesting fair items at the right time. Modeling personal preferences enables recommender systems to identify relevant subsets of items. These systems often rely on filtering techniques based on symbolic or numerical approaches in a stochastic context. In this paper, we focus on item-based collaborative filtering (CF) techniques. We show that it may be difficult to guarantee a good accuracy for the high values of prediction when ratings are not enough shared out on the rating scale. Thus, we propose a new approach combining a classic CF algorithm with an item association model to get better predictions. We deal with this issue by exploiting probalistic skewnesses in triplets of items. We validate our model by using the MovieLens dataset and get a significant improvement as regards the High MAE measure.
Clinical Implications of Fibroblast Activation Protein in Patients with Colon Cancer

Purpose: Human fibroblast activation protein (FAP)/seprase is a 97-kDa surface glycoprotein expressed on tumor associated fibroblasts in the majority of epithelial cancers including colon adenocarcinomas. FAP overexpression in human tumor cells has been shown to promote tumor growth in animal models, and clinical trials targeting FAP enzymatic activity have been initiated. The primary objective of this study was to evaluate the clinical significance of stromal FAP in human colon cancers by immunohistochemisty. Experimental Design: Sections of paraffin-embedded resected primary human colon cancer specimens from 1996 through 2001 within the Fox Chase Cancer Center tumor bank were stained with D8 antibody directed against FAP/seprase. Xenotransplanted human colorectal tumors in mice were examined similarly for stromal FAP in tumors of different sizes. Overall percentage of stromal FAP staining of the primary tumor was assessed semiquantitatively (0, 1+, 2+, 3+) and staining intensity was also graded (none, weak, intermediate, strong). Survival time and time to recurrence data were analyzed using Kaplan-Meier plots, log-rank tests, and Cox proportional hazards models. Results: One hundred thirty-eight patients with resected specimens were available for study (mean follow-up, 1,050 days) with 6 (4%) stage I, 52 (38%) stage II, 43 (31%) stage III, and 37 (27%) stage IV patients. FAP was detected in >93% of specimens. Semiquantitative staining was scored as 1+ in 28 (20%), 2+ in 52 (38%), and 3+ in 49 (35%). FAP staining intensity was graded as weak in 45 (33%), intermediate in 48 (35%), and dark in 36 (26%). Stromal FAP was found to correlate inversely with tumor stage (semiquantitative, P = 0.01; intensity, P = 0.009) and with tumor size of the tumor xenograft model (correlation coefficient, −0.61; P = 0.047), suggesting that stromal FAP may have a greater role in the early development of tumors. Furthermore, greater stromal FAP for patients with known metastatic disease was associated with a decreased survival. Conclusion: Our data indicate that patients whose colon tumors have high levels of stromal FAP are more likely to have aggressive disease progression and potential development of metastases or recurrence. This study affirms the rationale for ongoing clinical investigations using FAP as a therapeutic target to disrupt FAP-driven tumor progression in patients with metastatic disease. It also suggests that the effects of FAP inhibition should be investigated in earlier-stage tumors, given its high levels and potential effect earlier in the course of the disease.
College Athletes for Hire

Many books have been written on the evils of commercialism in college sport, and the hypocrisy of payments to athletes from alumni and other sources outside the university. Almost no attention, however, has been given to the way that the National Collegiate Athletic Association has embraced professionalism through its athletic scholarship policy. Because of this gap in the historical record, the NCAA is often cast as an embattled defender of amateurism, rather than as the architect of a nationwide money-laundering scheme. Sack and Staurowsky show that the NCAA formally abandoned amateurism in the 1950s and passed rules in subsequent years that literally transformed scholarship athletes into university employees. In addition, by purposefully fashioning an amateur mythology to mask the reality of this employer-employee relationship, the NCAA has done a disservice to student-athletes and to higher education. A major subtheme is that women, such as those who created the Association for Intercollegiate Athletics for Women (AIAW), opposed this hypocrisy, but lacked the power to sustain an alternative model. After tracing the evolution of college athletes into professional entertainers, and the harmful effects it has caused, the authors propose an alternative approach that places college sport on a firm educational foundation and defend the rights of both male and female college athletes. This is a provocative analysis for anyone interested in college sports in America and its subversion of traditional educational and amateur principles.
An Optimization Model for Fuzzy Binary Clustering

Clustering has been a powerful tool to visualize complex data with extensive applica- tions in many disciplines. In this paper, we propose an optimization-based solution to the fuzzy binary clustering problem by grouping all the data points into two clusters. Our model are based on two assumptions. One is that the similar objects are labeled similarly, which is known as the "cluster assumption" in semi-supervised learning. The other assumption is that the most dissimilar two objects belong to different clusters. The problem is formulated as a quadratic programming model and can seek the optimal fuzzy labels for the objects. Our model can be solved efficiently by designing a fast algorithm. In addition, it can be reformulated as a linear programming solved efficiently if the similarity matrix is sparse. Furthermore, this model can then be extended to explore the hard-binary-clustering and multiple-clustering problems by a few modifications. Experiments on both simulated and real data sets demonstrate the effectiveness of our method.
Managing welfare reform in New York City

Part 1 Foreword Part 2 Part One: Overview Chapter 3 Introduction to Welfare Reform Under Mayor Giuliani Chapter 4 Overview of Welfare Reform Part 5 Part Two: Elements of Welfare Reform Chapter 6 Changing the Organizational Culture Chapter 7 Protecting Against Welfare Fraud Chapter 8 Managing the Welfare System with JobStat Chapter 9 Achieving "Full Engagement" Chapter 10 Putting Welfare Applicants and Recipients to Work in the Work Experience Program Chapter 11 Placing Welfare Applicants and Recipients in Jobs Through Performance-Based Contracting Chapter 12 Engaging Drug and Alcohol Abusers Chapter 13 Housing the Homeless Part 14 Part Three: Results of Welfare Reform Chapter 15 The Welfare Revolution in New York City Chapter 16 Reflections of the Commissioner
Ecological Assessment of Autonomy in Instrumental Activities of Daily Living in Dementia Patients by the Means of an Automatic Video Monitoring System

Currently, the assessment of autonomy and functional ability involves clinical rating scales. However, scales are often limited in their ability to provide objective and sensitive information. By contrast, information and communication technologies may overcome these limitations by capturing more fully functional as well as cognitive disturbances associated with Alzheimer disease (AD). We investigated the quantitative assessment of autonomy in dementia patients based not only on gait analysis but also on the participant performance on instrumental activities of daily living (IADL) automatically recognized by a video event monitoring system (EMS). Three groups of participants (healthy controls, mild cognitive impairment, and AD patients) had to carry out a standardized scenario consisting of physical tasks (single and dual task) and several IADL such as preparing a pillbox or making a phone call while being recorded. After, video sensor data were processed by an EMS that automatically extracts kinematic parameters of the participants’ gait and recognizes their carried out activities. These parameters were then used for the assessment of the participants’ performance levels, here referred as autonomy. Autonomy assessment was approached as classification task using artificial intelligence methods that takes as input the parameters extracted by the EMS, here referred as behavioral profile. Activities were accurately recognized by the EMS with high precision. The most accurately recognized activities were “prepare medication” with 93% and “using phone” with 89% precision. The diagnostic group classifier obtained a precision of 73.46% when combining the analyses of physical tasks with IADL. In a further analysis, the created autonomy group classifier which obtained a precision of 83.67% when combining physical tasks and IADL. Results suggest that it is possible to quantitatively assess IADL functioning supported by an EMS and that even based on the extracted data the groups could be classified with high accuracy. This means that the use of such technologies may provide clinicians with diagnostic relevant information to improve autonomy assessment in real time decreasing observer biases.
An empirical study of end-user information system satisfaction using Doll and Torkzadeh instrument : The case of an Iranian power holding company

information systems within organizations is one of the most critical issues of information system management field. Considering the subjectivity of information system success, many surrogate measures have been developed by many researchers. End-user information system satisfaction (EUISS) is probably the most widely used measure of information system success. It can be defined as the overall evaluation of an end-user regarding his/her experience related with the information system. In this paper we use a 12-item instrument developed by Doll and Torkzadeh to study EUISS. This instrument has been accepted in literature vastly and measures the satisfaction of information systems end-users in five different dimensions: content, accuracy, format, ease of use and timeliness. However, to date, this instrument has not been tested in an Iranian setting. The instrument has been applied in an Iranian power holding company. A sample of end-users has been taken and asked to answer to a pre-designed questionnaire. Then, validity of the questionnaire is evaluated through convergent validity and reliability tests. Discriminant analysis has also been applied. After the validity of the questionnaire is confirmed, Kruskal-Wallis and two-way ANOVA tests are applied to analyze the results.
Towards Context Oriented Web Services for Smart Personal Object Technologies ( COWSPOTS )

Research in the area of Context-Awareness has tradi tionally focused on location, time, and proximity-based context sensing. Advances in wirele ss networking technology and in the miniaturization of computing hardware now allow us to contemplate more expansive utilizations of contextual information. In this paper, we advoc ate the use of Web services as the basis for the next generation of context aware applications. Web s rvices potentially offer unprecedented cross-platform interoperability and can be used to broaden the range of context indicators and services for mobile devices. Also in this paper, w e introduce the COWSPOTS project, a research initiative that seeks to apply context-aware Web se rvic s to the medical domain.