snu-aidas/HVMap-dataset huggingface dataset:
Reduced graphene oxide–silver nanoparticle nanocomposite: a potential anticancer nanotherapy

BACKGROUND
Graphene and graphene-based nanocomposites are used in various research areas including sensing, energy storage, and catalysis. The mechanical, thermal, electrical, and biological properties render graphene-based nanocomposites of metallic nanoparticles useful for several biomedical applications. Epithelial ovarian carcinoma is the fifth most deadly cancer in women; most tumors initially respond to chemotherapy, but eventually acquire chemoresistance. Consequently, the development of novel molecules for cancer therapy is essential. This study was designed to develop a simple, non-toxic, environmentally friendly method for the synthesis of reduced graphene oxide-silver (rGO-Ag) nanoparticle nanocomposites using Tilia amurensis plant extracts as reducing and stabilizing agents. The anticancer properties of rGO-Ag were evaluated in ovarian cancer cells.


METHODS
The synthesized rGO-Ag nanocomposite was characterized using various analytical techniques. The anticancer properties of the rGO-Ag nanocomposite were evaluated using a series of assays such as cell viability, lactate dehydrogenase leakage, reactive oxygen species generation, cellular levels of malonaldehyde and glutathione, caspase-3 activity, and DNA fragmentation in ovarian cancer cells (A2780).


RESULTS
AgNPs with an average size of 20 nm were uniformly dispersed on graphene sheets. The data obtained from the biochemical assays indicate that the rGO-Ag nanocomposite significantly inhibited cell viability in A2780 ovarian cancer cells and increased lactate dehydrogenase leakage, reactive oxygen species generation, caspase-3 activity, and DNA fragmentation compared with other tested nanomaterials such as graphene oxide, rGO, and AgNPs.


CONCLUSION
T. amurensis plant extract-mediated rGO-Ag nanocomposites could facilitate the large-scale production of graphene-based nanocomposites; rGO-Ag showed a significant inhibiting effect on cell viability compared to graphene oxide, rGO, and silver nanoparticles. The nanocomposites could be effective non-toxic therapeutic agents for the treatment of both cancer and cancer stem cells.
Inferring Undiscovered Public Knowledge by Using Text Mining-driven Graph Model

Due to the recent development of Information Technology, the number of publications is increasing exponentially. In response to the increasing number of publications, there has been a sharp surge in the demand for replacing the existing manual text data processing by an automatic text data processing. Swanson proposed ABC model [1] on the top of text mining as a part of literature-based knowledge discovery for finding new possible biomedical hypotheses about three decades ago. The following clinical scholars proved the effectiveness of the possible hypotheses found by ABC model [2]. Such effectiveness let scholars try various literature-based knowledge discovery approaches [3, 4, 5]. However, their trials are not fully automated but hybrids of automatic and manual processes. The manual process requires the intervention of experts. In addition, their trials consider a single perspective. Even trials involving network theory have difficulties in mal-understanding the entire network structure of the relationships among concepts and the systematic interpretation on the structure [6, 7]. Thus, this study proposes a novel approach to discover various relationships by extending the intermediate concept B to a multi-leveled concept. By applying a graph-based path finding method based on co-occurrence and the relational entities among concepts, we attempt to systematically analyze and investigate the relationships between two concepts of a source node and a target node in the total paths. For the analysis of our study, we set our baseline as the result of Swanson [8]'s work. This work suggested the intermediate concept or terms between Raynaud's disease and fish oils as blood viscosity, platelet aggregability, and vasconstriction. We compared our results of intermediate concepts with these intermediate concepts of Swanson's. This study provides distinct perspectives for literature-based discovery by not only discovering the meaningful relationship among concepts in biomedical literature through graph-based path interference but also being able to generate feasible new hypotheses.
Comparison of Hilbert transform and wavelet methods for the analysis of neuronal synchrony

The quantification of phase synchrony between neuronal signals is of crucial importance for the study of large-scale interactions in the brain. Two methods have been used to date in neuroscience, based on two distinct approaches which permit a direct estimation of the instantaneous phase of a signal [Phys. Rev. Lett. 81 (1998) 3291; Human Brain Mapping 8 (1999) 194]. The phase is either estimated by using the analytic concept of Hilbert transform or, alternatively, by convolution with a complex wavelet. In both methods the stability of the instantaneous phase over a window of time requires quantification by means of various statistical dependence parameters (standard deviation, Shannon entropy or mutual information). The purpose of this paper is to conduct a direct comparison between these two methods on three signal sets: (1) neural models; (2) intracranial signals from epileptic patients; and (3) scalp EEG recordings. Levels of synchrony that can be considered as reliable are estimated by using the technique of surrogate data. Our results demonstrate that the differences between the methods are minor, and we conclude that they are fundamentally equivalent for the study of neuroelectrical signals. This offers a common language and framework that can be used for future research in the area of synchronization.
A General Agnostic Active Learning Algorithm

We present a simple, agnostic active learning algorithm that works for any hypothesis class of bounded VC dimension, and any data distribution. Our algorithm extends a scheme of Cohn, Atlas, and Ladner [6] to the agnostic setting, by (1) reformulating it using a reduction to supervised learning and (2) showing how to apply generalization bounds even for the non-i.i.d. samples that result from selective sampling. We provide a general characterization of the label complexity of our algorithm. This quantity is never more than the usual PAC sample complexity of supervised learning, and is exponentially smaller for some hypothesis classes and distributions. We also demonstrate improvements experimentally.
Examining the critical success factors in the adoption of enterprise resource planning

This paper presents a literature review of the critical success factors (CSFs) in the implementation of enterprise resource planning (ERP) across 10 different countries/regions. The review covers journals, conference proceedings, doctoral dissertation, and textbooks from these 10 different countries/regions. Through a review of the literature, 18 CSFs were identified, with more than 80 sub-factors, for the successful implementation of ERP. The findings of our study reveal that ‘appropriate business and IT legacy systems’, ‘business plan/vision/goals/justification’, ‘business process reengineering’, ‘change management culture and programme’, ‘communication’, ‘ERP teamwork and composition’, ‘monitoring and evaluation of performance’, ‘project champion’, ‘project management’, ‘software/system development, testing and troubleshooting’, ‘top management support’, ‘data management’, ‘ERP strategy and implementation methodology’, ‘ERP vendor’, ‘organizational characteristics’, ‘fit between ERP and business/process’, ‘national culture’ and ‘country-related functional requirement’ were the commonly extracted factors across these 10 countries/regions. In these 18 CSFs, ‘top management support’ and ‘training and education’ were the most frequently cited as the critical factors to the successful implementation of ERP systems. # 2008 Elsevier B.V. All rights reserved.
Using Quality Models in Software Package Selection

0 7 4 0 7 4 5 9 / 0 3 / $ 1 9 . 0 0 © 2 0 0 3 I E E E All the methodologies that have been proposed recently for choosing software packages compare user requirements with the packages’ capabilities.3–5 There are different types of requirements, such as managerial, political, and, of course, quality requirements. Quality requirements are often difficult to check. This is partly due to their nature, but there is another reason that can be mitigated, namely the lack of structured and widespread descriptions of package domains (that is, categories of software packages such as ERP systems, graphical or data structure libraries, and so on). This absence hampers the accurate description of software packages and the precise statement of quality requirements, and consequently overall package selection and confidence in the result of the process. Our methodology for building structured quality models helps solve this drawback. (See the “Related Work” sidebar for information about other approaches.) A structured quality model for a given package domain provides a taxonomy of software quality features, and metrics for computing their value. Our approach relies on the International Organization for Standardization and International Electrotechnical Commission 9126-1 quality standard,6 which we selected for the following reasons:
PubChem Substance and Compound databases

PubChem (https://pubchem.ncbi.nlm.nih.gov) is a public repository for information on chemical substances and their biological activities, launched in 2004 as a component of the Molecular Libraries Roadmap Initiatives of the US National Institutes of Health (NIH). For the past 11 years, PubChem has grown to a sizable system, serving as a chemical information resource for the scientific research community. PubChem consists of three inter-linked databases, Substance, Compound and BioAssay. The Substance database contains chemical information deposited by individual data contributors to PubChem, and the Compound database stores unique chemical structures extracted from the Substance database. Biological activity data of chemical substances tested in assay experiments are contained in the BioAssay database. This paper provides an overview of the PubChem Substance and Compound databases, including data sources and contents, data organization, data submission using PubChem Upload, chemical structure standardization, web-based interfaces for textual and non-textual searches, and programmatic access. It also gives a brief description of PubChem3D, a resource derived from theoretical three-dimensional structures of compounds in PubChem, as well as PubChemRDF, Resource Description Framework (RDF)-formatted PubChem data for data sharing, analysis and integration with information contained in other databases.
Image Steganography Using LSB and Edge – Detection Technique

217  Abstract-Steganography is the technique of hiding the fact that communication is taking place, by hiding data in other data. Many different carrier file formats can be used, but digital images are the most popular because of their frequency on the Internet. For hiding secret information in images, there exist a large variety of steganographic techniques some are more complex than others and all of them have respective strong and weak points. Steganalysis, the detection of this hidden information, is an inherently difficult problem and requires a thorough investigation so we are using " Edge detection Filter ". In this paper search how the edges of the images can be used to hiding text message in Steganography .It give the depth view of image steganography and Edge detection Filter techniques. Method: In this paper search how the edges of the images can be used to hiding text message in Steganography. For that gray image has been presented. In this method tried to find binary value of each character of text message and then in the next stage, tried to find dark places of gray image (black) by converting the original image to binary image for labeling each object of image by considering on 8 pixel connectivity. Then these images have been converted to RGB image in order to find dark places. Because in this way each sequence of gray color turns into RGB color and dark level of grey image is found by this way if the Gary image is very light the histogram must be changed manually to find just dark places. In the final stage each 8 pixels of dark places has been considered as a byte and binary value of each character has been put in low bit of each byte that was created manually by dark places pixels for increasing security of the main way of least Significant bit steganography. Steganalysis then used to evaluate the hiding process to ensure the data can be hidden in best possible way.
Clustal W and Clustal X version 2.0

SUMMARY
The Clustal W and Clustal X multiple sequence alignment programs have been completely rewritten in C++. This will facilitate the further development of the alignment algorithms in the future and has allowed proper porting of the programs to the latest versions of Linux, Macintosh and Windows operating systems.


AVAILABILITY
The programs can be run on-line from the EBI web server: http://www.ebi.ac.uk/tools/clustalw2. The source code and executables for Windows, Linux and Macintosh computers are available from the EBI ftp site ftp://ftp.ebi.ac.uk/pub/software/clustalw2/
Evaluating three treatments for borderline personality disorder: a multiwave study.

OBJECTIVE
The authors examined three yearlong outpatient treatments for borderline personality disorder: dialectical behavior therapy, transference-focused psychotherapy, and a dynamic supportive treatment.


METHOD
Ninety patients who were diagnosed with borderline personality disorder were randomly assigned to transference-focused psychotherapy, dialectical behavior therapy, or supportive treatment and received medication when indicated. Prior to treatment and at 4-month intervals during a 1-year period, blind raters assessed the domains of suicidal behavior, aggression, impulsivity, anxiety, depression, and social adjustment in a multiwave study design.


RESULTS
Individual growth curve analysis revealed that patients in all three treatment groups showed significant positive change in depression, anxiety, global functioning, and social adjustment across 1 year of treatment. Both transference-focused psychotherapy and dialectical behavior therapy were significantly associated with improvement in suicidality. Only transference-focused psychotherapy and supportive treatment were associated with improvement in anger. Transference-focused psychotherapy and supportive treatment were each associated with improvement in facets of impulsivity. Only transference-focused psychotherapy was significantly predictive of change in irritability and verbal and direct assault.


CONCLUSIONS
Patients with borderline personality disorder respond to structured treatments in an outpatient setting with change in multiple domains of outcome. A structured dynamic treatment, transference-focused psychotherapy was associated with change in multiple constructs across six domains; dialectical behavior therapy and supportive treatment were associated with fewer changes. Future research is needed to examine the specific mechanisms of change in these treatments beyond common structures.
Using machine learning algorithms for housing price prediction: The case of Fairfax County, Virginia housing data

House sales are determined based on the Standard & Poor’s Case-Shiller home price indices and the housing price index of the Office of Federal Housing Enterprise Oversight (OFHEO). These reflect the trends of the US housing market. In addition to these housing price indices, the development of a housing price prediction model can greatly assist in the prediction of future housing prices and the establishment of real estate policies. This study uses machine learning algorithms as a research methodology to develop a housing price prediction model. To improve the accuracy of housing price prediction, this paper analyzes the housing data of 5359 townhouses in Fairfax County, Virginia, gathered by the Multiple Listing Service (MLS) of the Metropolitan Regional Information Systems (MRIS). We develop a housing price prediction model based on machine learning algorithms such as C4.5, RIPPER, Naïve Bayesian, and AdaBoost and compare their classification accuracy performance. We then propose an improved housing price prediction model to assist a house seller or a real estate agent make better informed decisions based on house price valuation. The experiments demonstrate that the RIPPER algorithm, based on accuracy, consistently outperforms the other models in the performance of housing price prediction. 2014 Elsevier Ltd. All rights reserved.
3D Sampling Textures for Creative Design and Manufacturing

1 Texture synthesized from 3D scans of snake-skin and mushroom laminae. ABSTRACT 3D sampling is a robust new strategy for exploring and creating designs. 3D textures are sampled and mixed almost like music to create new multifunctional surfaces and material microstructures (Figure 1). This paper presents several design cases performed using 3D sampling techniques, demonstrating how they can be used to explore and enhance product ideas, variations, and functions in subtle and responsive ways. In each case, design variations are generated and their mechanical behavior is evaluated against performance criteria using computational simulation or empirical testing. This work aims to promote creativity and discovery by introducing irregular geometric structures within trial-and-error feedback loops. Sayjel Vijay Patel SUTD DManD Centre
Metaphor in the Mind : The Cognition of Metaphor

The most sustained and innovative recent work on metaphor has occurred in cognitive science and psychology. Psycholinguistic investigation suggests that novel, poetic metaphors are processed differently than literal speech, while relatively conventionalized and contextually salient metaphors are processed more like literal speech. This conflicts with the view of “cognitive linguists” like George Lakoff that all or nearly all thought is essentially metaphorical. There are currently four main cognitive models of metaphor comprehension: juxtaposition, category-transfer, feature-matching, and structural alignment. Structural alignment deals best with the widest range of examples; but it still fails to account for the complexity and richness of fairly novel, poetic metaphors. 1. General Issues in the Study of Metaphor Philosophers have often adopted a dismissive attitude toward metaphor. Hobbes (ch. 8) advocated excluding metaphors from rational discourse because they “openly profess deceit,” while Locke (Bk. 3, ch. 10) claimed that figurative uses of language serve only “to insinuate wrong ideas, move the passions, and thereby mislead the judgment; and so indeed are perfect cheats.” Later, logical positivists like Ayer and Carnap assumed that because metaphors like (1) How sweet the moonlight sleeps upon this bank!2 involve category mistakes, they have no real meaning or verification conditions. Thus, they too mentioned metaphor only to place it beyond the pale of rational discourse. Starting in the 1960s and 70s, philosophers and linguists began to take more positive interest in metaphor. Black argued forcefully that metaphors do have a distinctive, essentially non-propositional meaning or cognitive significance, which is produced by the “interaction” of the “systems of associated commonplaces” for the metaphor’s “primary” and “secondary” subjects (e.g., with moonlight and sleeping sweetly). Other theorists were more friendly to the idea that metaphorical and literal meaning are of the same essential kind. Many of them proposed that the literal absurdity of metaphors © Blackwell Publishing 2006 Philosophy Compass 1/2 (2006): 154–170, 10.1111/j.1747-9991.2006.00013.x
Improvement of Intrusion Detection System in Data Mining using Neural Network

Many researchers have argued that Artificial Neural Networks (ANNs) can improve the performance of intrusion detection systems (IDS). One of the central areas in network intrusion detection is how to build effective systems that are able to distinguish normal from intrusive traffic. In this paper four different algorithms are used namely as Multilayer Perception, Radial Base Function, Logistic Regression and Voted Perception. All these neural based algorithms are implemented in WEKA data mining tool to evaluate the performance. For experimental work, NSL KDD dataset is used. Each neural based algorithm is tested with conducted dataset. It is shown that the Multilayer Perception neural network algorithm is providing more accurate results than other algorithms. Keywords— Data Mining, Intrusion Detection System, Neural network classifier algorithm, NSL KDD dataset
Valid items for screening dysphagia risk in patients with stroke: a systematic review.

BACKGROUND AND PURPOSE
Screening for dysphagia is essential to the implementation of preventive therapies for patients with stroke. A systematic review was undertaken to determine the evidence-based validity of dysphagia screening items using instrumental evaluation as the reference standard.


METHODS
Four databases from 1985 through March 2011 were searched using the terms cerebrovascular disease, stroke deglutition disorders, and dysphagia. Eligibility criteria were: homogeneous stroke population, comparison to instrumental examination, clinical examination without equipment, outcome measures of dysphagia or aspiration, and validity of screening items reported or able to be calculated. Articles meeting inclusion criteria were evaluated for methodological rigor. Sensitivity, specificity, and predictive capabilities were calculated for each item.


RESULTS
Total source documents numbered 832; 86 were reviewed in full and 16 met inclusion criteria. Study quality was variable. Testing swallowing, generally with water, was the most commonly administered item across studies. Both swallowing and nonswallowing items were identified as predictive of aspiration. Neither swallowing protocols nor validity were consistent across studies.


CONCLUSIONS
Numerous behaviors were found to be associated with aspiration. The best combination of nonswallowing and swallowing items as well as the best swallowing protocol remains unclear. Findings of this review will assist in development of valid clinical screening instruments.
Structure, culture and Simmelian ties in entrepreneurial firms

This article develops a cultural agreement approach to organizational culture that emphasizes how clusters of individuals reinforce potentially idiosyncratic understandings of many aspects of culture including the structure of network relations. Building on recent work concerning Simmelian tied dyads (defined as dyads embedded in three-person cliques), the research examines perceptions concerning advice and friendship relations in three entrepreneurial firms. The results support the idea that Simmelian tied dyads (relative to dyads in general) reach higher agreement concerning who is tied to whom, and who are embedded together in triads in organizations. © 2002 Elsevier Science B.V. All rights reserved.
Surface reconstruction from unorganized points

Computer Graphics, 26, 2, July 1992 Surface Reconstruction from Unorganized Points Hugues Hoppe* Tony DeRose* Tom Duchampt John McDonald$ Werner Stuetzle~ University of Washington Seattle, WA 98195 We describe and demonstrate an algorithm that takes as input an unorganized set of points {xl, . . . . x.} c IR3 on or near an unknown manifold M, and produces as output a simplicial surface that approximates M. Neither the topology, the presence of boundaries, nor the geometry of M are assumed to be known in advance — all are inferred automatically from the data. This problem natu rally arises in a variety of practical situations such as range scanning an object from multiple view points, recovery of biological shapes from two-dimensional slices, and interactive surface sketching. CR