snu-aidas/HVMap-dataset huggingface dataset:
Transcutaneous measurement of glomerular filtration rate using FITC-sinistrin in rats.

BACKGROUND
Inulin/sinistrin (I/S) clearance is a gold standard for an accurate assessment of glomerular filtration rate (GFR). Here we describe and validate an approach for a transcutaneous determination of GFR by using fluorescein-isothiocyanate-labelled sinistrin (FITC-S) in rats.


METHODS
Using a small animal imager, fluorescence is measured over the depilated ear of a rat after the injection of FITC-S. The decay curve of fluorescence is used for the calculation of half-life and GFR. The thus obtained transcutaneous data were validated by simultaneously performed enzymatic and fluorometric measurements in plasma of both FITC-S and sinistrin.


RESULTS
The results of enzymatic sinistrin determination versus transcutaneous half-life of FITC-S or plasma fluorescence correlated well with each other (R(2) > 0.90). Furthermore, Bland-Altman analyses proved a good degree of agreement of the three methods used. The measurements performed in healthy animals as well as different models of renal failure demonstrate its appropriateness in a wide range of renal function.


CONCLUSIONS
The transcutaneous method described offers a precise assessment of GFR in small animals. As neither blood and/or urine sampling nor time-consuming lab work is required, GFR can be determined immediately after the clearance procedure is finished. This method, therefore, simplifies and fastens GFR determinations in small lab animals compared to conventional bolus clearance techniques based on blood sampling. A low-cost device for the measurement of transcutaneous fluorescence intensity over time is under construction.
ntology matching with semantic verification ves

Automated Semantic Matching of Ontologies with Verification (ASMOV) is a novel algorithm that uses lexical and structural characteristics of two ontologies to iteratively calculate a similarity measure between them, derives an alignment, and then verifies it to ensure that it does not contain semantic inconsistencies. In this paper, we describe the ASMOV algorithm, and then present experimental results that measure vailable online xxx eywords: ntology ntology alignment ntology matching its accuracy using the OAEI 2008 tests, and that evaluate its use with two different thesauri: WordNet, and the Unified Medical Language System (UMLS). These results show the increased accuracy obtained by combining lexical, structural and extensional matchers with semantic verification, and demonstrate the advantage of using a domain-specific thesaurus for the alignment of specialized ontologies. © 2009 Elsevier B.V. All rights reserved.
of Aperture Coupled Microstrip Antennas : History , Operation , Development , and Applications
Discrete-time signal processing (2nd ed.)
Least-Squares Fitting of Circles and Ellipses ∗

Fitting circles and ellipses to given points in the plane is a problem that arises in many application areas, e.g. computer graphics [1], coordinate metrology [2], petroleum engineering [11], statistics [7]. In the past, algorithms have been given which fit circles and ellipses in some least squares sense without minimizing the geometric distance to the given points [1], [6]. In this paper we present several algorithms which compute the ellipse for which the sum of the squares of the distances to the given points is minimal. These algorithms are compared with classical simple and iterative methods. Circles and ellipses may be represented algebraically i.e. by an equation of the form F (x) = 0. If a point is on the curve then its coordinates x are a zero of the function F . Alternatively, curves may be represented in parametric form, which is well suited for minimizing the sum of the squares of the distances. 1 Preliminaries and Introduction Ellipses, for which the sum of the squares of the distances to the given points is minimal will be referred to as “best fit” or “geometric fit”, and the algorithms will be called “geometric”. Determining the parameters of the algebraic equation F (x) = 0 in the least squares sense will be denoted by “algebraic fit” and the algorithms will be called “algebraic”. We will use the well known Gauss-Newton method to solve the nonlinear least squares problem (cf. [15]). Let u = (u1, . . . , un) T be a vector of unknowns and consider the nonlinear system of m equations f(u) = 0. If m > n, then we want to minimize
Measures of retaining digital evidence to prosecute computer-based cyber-crimes

With the rapid growth of computer and network systems in recent years, there has also been a corresponding increase in cyber-crime. Cybercrime takes many forms and has garnered much attention in the media, making information security a more urgent and important priority. In order to fight cyber-crime, criminal evidence must be gathered from these computer-based systems. This is quite different from the collection of conventional criminal evidence and can confuse investigators attempting to deal with the forensics of cyber-crime, highlighting the importance of computer forensics. In this paper, we offer solutions to guard against cyber-crime through the implementation of software toolkits for computerbased systems. In this way, those who engage in criminal acts in cyber-space can be more easily apprehended. © 2006 Elsevier B.V. All rights reserved.
Obesity, fat distribution, and weight gain as risk factors for clinical diabetes in men.

OBJECTIVE
To investigate the relation between obesity, fat distribution, and weight gain through adulthood and the risk of non-insulin-dependent diabetes mellitus (NIDDM).


RESEARCH DESIGN AND METHODS
We analyzed data from a cohort of 51,529 U.S. male health professionals, 40-75 years of age in 1986, who completed biennial questionnaires sent out in 1986, 1988, 1990, and 1992. During 5 years of follow-up (1987-1992), 272 cases of NIDDM were diagnosed among men without a history of diabetes, heart disease, and cancer in 1986 and who provided complete health information. Relative risks (RRs) associated with different anthropometric measures were calculated controlling for age, and multivariate RRs were calculated controlling for smoking, family history of diabetes, and age.


RESULTS
We found a strong positive association between overall obesity as measured by body mass index (BMI) and risk of diabetes. Men with a BMI of > or = 35 kg/m2 had a multivariate RR of 42.1 (95% confidence interval [CI] 22.0-80.6) compared with men with a BMI < 23.0 kg/m2. BMI at age 21 and absolute weight gain throughout adulthood were also significant independent risk factors for diabetes. Fat distribution, measured by waist-to-hip ratio (WHR), was a good predictor of diabetes only among the top 5%, while waist circumference was positively associated with the risk of diabetes among the top 20% of the cohort.


CONCLUSIONS
These data suggest that waist circumference may be a better indicator than WHR of the relationship between abdominal adiposity and risk of diabetes. Although early obesity, absolute weight gain throughout adulthood, and waist circumference were good predictors of diabetes, attained BMI was the dominant risk factor for NIDDM; even men of average relative weight had significantly elevated RRs.
Digital Forensic Model Based On Malaysian Investigation Process

Faculty Of Science & Technology Islamic Science University Of Malaysia Summary With the proliferation of the digital crime around the world, numerous digital forensic investigation models already being develop .In fact many of the digital forensic investigation model focus on technical implementation of the investigation process as most of it develop by traditional forensic expert and technologist. As an outcome of this problem most of the digital forensic practitioners focus on technical aspect and forget the core concept of digital forensic investigation model .In this paper we are introducing a new digital forensic model which will be capture a full scope of an investigation process based on Malaysia Cyber Law .The proposed model is also compared with the existing model which currently available and being apply in the investigation process.
Differentially Private Online Learning

In this paper, we consider the problem of preserving privacy in the context of online learning. Online learning involves learning from data in real-time, due to which the learned model as well as its predictions are continuously changing. This makes preserving privacy of each data point significantly more challenging as its effect on the learned model can be easily tracked by observing changes in the subsequent predictions. Furthermore, with more and more online systems (e.g. search engines like Bing, Google etc.) trying to learn their customers’ behavior by leveraging their access to sensitive customer data (through cookies etc.), the problem of privacy preserving online learning has become critical. We study the problem in the framework of online convex programming (OCP)—a popular online learning setting with several theoretical and practical implications—while using differential privacy as the formal measure of privacy. For this problem, we provide a generic framework that can be used to convert any given OCP algorithm into a private OCP algorithm with provable privacy as well as regret guarantees (utility), provided that the given OCP algorithm satisfies the following two criteria: 1) linearly decreasing sensitivity, i.e., the effect of the new data points on the learned model decreases linearly, 2) sub-linear regret. We then illustrate our approach by converting two popular OCP algorithms into corresponding differentially private algorithms while guaranteeing Õ( √ T ) regret for strongly convex functions. Next, we consider the practically important class of online linear regression problems, for which we generalize the approach by Dwork et al. (2010a) to provide a differentially private algorithm with just poly-log regret. Finally, we show that our online learning framework can be used to provide differentially private algorithms for the offline learning problem as well. For the offline learning problem, our approach guarantees better error bounds and is more practical than the existing state-of-the-art methods (Chaudhuri et al., 2011; Rubinstein et al., 2009).
Telemanipulation of Snake-Like Robots for Minimally Invasive Surgery of the Upper Airway

Abstract. This research focuses on developing and testing the highlevel control of a novel eight DOF hybrid robot using a DaVinci master manipulator. The teleoperation control is formulated as weighted, multi objective constrained least square (LS) optimization problems one for the master controller and the other for the slave controller. This allows us to incorporate various virtual fixtures in our control algorithm as constraints of the LS problem based on the robot environment. Experimental validation to ensure position tracking and sufficient dexterity to perform suturing in confined spaces such as throat are presented.
An Inside Look at Botnets

The continued growth and diversification of the Internet has been accompanied by an increasing prevalence of attacks and intrusions [40]. It can be argued, however, that a significant change in motivation for malicious activi ty has taken place over the past several years: from vandalism and recognition in th e hacker community, to attacks and intrusions for financial gain. This shift has bee n marked by a growing sophistication in the tools and methods used to conduct atta cks, thereby escalating the network security arms race. Our thesis is that the reactivemethods for network security that are predominant today are ultimately insufficient and that more proactivemethods are required. One such approach is to develop a foundational understanding of the mechanisms employed by malicious software (malware) which is often readi ly available in source form on the Internet. While it is well known that large IT secu rity companies maintain detailed databases of this information, these are not o penly available and we are not aware of any such open repository. In this paper we begin t he process of codifying the capabilities of malware by dissecting four widely-u sed Internet Relay Chat (IRC) botnet codebases. Each codebase is classified along se ven k y dimensions including botnet control mechanisms, host control mechani sms, propagation mechanisms, exploits, delivery mechanisms, obfuscation and de ception mechanisms. Our study reveals the complexity of botnet software, and we disc us es implications for defense strategies based on our analysis.
Mining and ranking users’ intents behind queries

How to understand intents behind user queries is crucial towards improving the performance of Web search systems. NTCIR-11 IMine task focuses on this problem. In this paper, we address the NTCIR-11 IMine task with two phases referred to as Query Intent Mining (QIM) and Query Intent Ranking (QIR). (I) QIM is intended to mine users’ potential intents by clustering short text fragments related to the given query. (II) QIR focuses on ranking those mined intents in a proper way. Two challenges exist in handling these tasks. (II) How to precisely estimate the intent similarity between user queries which only consist of a few words. (2) How to properly rank intents in terms of multiple factors, e.g. relevance, diversity, intent drift and so on. For the first challenge, we first investigate two interesting phenomena by analyzing query logs and document datasets, namely “Same-Intent-Co-Click” (SICC) and “Same-Intent-Similar-Rank” (SISR). SICC means that when users issue different queries, these queries represent the same intent if they click on the same URL. SISR means that if two queries denote the same intent, we should get similar search results when issuing them to a search engine. Then, we propose similarity functions for QIM based on the two phenomena. For the second challenge, we propose a novel intent ranking model which considers multiple factors as a whole. We perform extensive experiments and an interesting case study on the Chinese dataset of NTCIR-11 IMine task. Experimental results demonstrate the effectiveness of our proposed approaches in terms of both QIM and QIR.
3-D TCAD simulation to optimize the trench termination design for higher and robust BVdss

Optimizing the edge termination design around the periphery of active area is critically important for achieving the highest and stable breakdown voltage (BVDSS) for any power devices. Active cell structures can be assumed as two dimensional (2-D) in the central part of the die, however as the active cells terminate to the termination regions at the periphery of the die, 2-D and 3-D transition regions are formed at different locations of the die layout with respect to the last edge termination trench. Optimization of the 3-D termination region is imperative to ascertain equal or higher BVDSS of the termination region than the active cell region. Synopsys advanced multi-dimensional TCAD device simulation tool - “Sentaurus Device Editor (SDE) [1]” is adopted for designing and optimizing the 3-D termination transition region for a higher and robust BVDSS, which is validated by the experimental data.
A Comparison of Tactile, Visual, and Auditory Warnings for Rear-End Collision Prevention in Simulated Driving

OBJECTIVE
This study examined the effectiveness of rear-end collision warnings presented in different sensory modalities as a function of warning timing in a driving simulator.


BACKGROUND
The proliferation of in-vehicle information and entertainment systems threatens driver attention and may increase the risk of rear-end collisions. Collision warning systems have been shown to improve inattentive and/or distracted driver response time (RT) in rear-end collision situations. However, most previous rear-end collision warning research has not directly compared auditory, visual, and tactile warnings.


METHOD
Sixteen participants in a fixed-base driving simulator experienced four warning conditions: no warning, visual, auditory, and tactile. The warnings activated when the time-to-collision (TTC) reached a critical threshold of 3.0 or 5.0 s. Driver RT was captured from a warning below critical threshold to brake initiation.


RESULTS
Drivers with a tactile warning had the shortest mean RT. Drivers with a tactile warning had significantly shorter RT than drivers without a warning and had a significant advantage over drivers with visual warnings.


CONCLUSION
Tactile warnings show promise as effective rear-end collision warnings.


APPLICATION
The results of this study can be applied to the future design and evaluation of automotive warnings designed to reduce rear-end collisions.
Comparative Metagenomics Reveals Host Specific Metavirulomes and Horizontal Gene Transfer Elements in the Chicken Cecum Microbiome

BACKGROUND
The complex microbiome of the ceca of chickens plays an important role in nutrient utilization, growth and well-being of these animals. Since we have a very limited understanding of the capabilities of most species present in the cecum, we investigated the role of the microbiome by comparative analyses of both the microbial community structure and functional gene content using random sample pyrosequencing. The overall goal of this study was to characterize the chicken cecal microbiome using a pathogen-free chicken and one that had been challenged with Campylobacter jejuni.


METHODOLOGY/PRINCIPAL FINDINGS
Comparative metagenomic pyrosequencing was used to generate 55,364,266 bases of random sampled pyrosequence data from two chicken cecal samples. SSU rDNA gene tags and environmental gene tags (EGTs) were identified using SEED subsystems-based annotations. The distribution of phylotypes and EGTs detected within each cecal sample were primarily from the Firmicutes, Bacteroidetes and Proteobacteria, consistent with previous SSU rDNA libraries of the chicken cecum. Carbohydrate metabolism and virulence genes are major components of the EGT content of both of these microbiomes. A comparison of the twelve major pathways in the SEED Virulence Subsystem (metavirulome) represented in the chicken cecum, mouse cecum and human fecal microbiomes showed that the metavirulomes differed between these microbiomes and the metavirulomes clustered by host environment. The chicken cecum microbiomes had the broadest range of EGTs within the SEED Conjugative Transposon Subsystem, however the mouse cecum microbiomes showed a greater abundance of EGTs in this subsystem. Gene assemblies (32 contigs) from one microbiome sample were predominately from the Bacteroidetes, and seven of these showed sequence similarity to transposases, whereas the remaining sequences were most similar to those from catabolic gene families.


CONCLUSION/SIGNIFICANCE
This analysis has demonstrated that mobile DNA elements are a major functional component of cecal microbiomes, thus contributing to horizontal gene transfer and functional microbiome evolution. Moreover, the metavirulomes of these microbiomes appear to associate by host environment. These data have implications for defining core and variable microbiome content in a host species. Furthermore, this suggests that the evolution of host specific metavirulomes is a contributing factor in disease resistance to zoonotic pathogens.
Interactive Graph Cuts for Optimal Boundary and Region Segmentation of Objects in N-D Images

In this paper we describe a new technique for general purpose interactive segmentation of N-dimensional images . The user marks certain pixels as “object” or “background” to provide hard constraints for segmentation. Additional soft constraints incorporate both boundary and region information. Graph cuts are used to find the globally optimal segmentation of the N-dimensional image. The obtained solution gives the best balance of boundary and region properties among all segmentations satisfying the constraints . The topology of our segmentation is unrestricted and both “object” and “background” segments may consist of several isolated parts. Some experimental results are present ed in the context of photo/video editing and medical image segmentation. We also demonstrate an interesting Gestalt example. A fast implementation of our segmentation method is possible via a new max-flow algorithm in [2].
Corporate Governance and Corporate Social Responsibility Synergies and Interrelationships

Manuscript Type: Empirical Research Questions/Issue: This paper seeks to explore the interrelationships between corporate governance (CG) and corporate social responsibility (CSR): first, theoretically, by reviewing the literature and surveying various postulations on offer; second, empirically, by investigating the conception and interpretation of this relationship in the context of a sample of firms operating in Lebanon. Accordingly, the paper seeks to highlight the increasing cross-connects or interfaces between CG and CSR, capitalizing on fresh insights from a developing country perspective. Research Findings/Results: A qualitative interpretive research methodology was adopted, drawing on in-depth interviews with the top managers of eight corporations operating in Lebanon, with the findings suggesting that the majority of managers conceive of CG as a necessary pillar for sustainable CSR. These findings are significant and interesting, implying that recent preoccupation with CG in developing countries is starting to be counterbalanced by some interest/attention to CSR, with growing appreciation of their interdependencies and the need to move beyond CG conformance toward voluntary CSR performance. Theoretical Implications: This study makes two important contributions. First, it suggests that there is a salient two-way relationship and increasing overlap between CG and CSR. While much previous literature has researched CG and CSR independently, this paper makes the case for considering them jointly and systematically. Second, the paper outlines a number of theoretical propositions that can serve as the basis for future research on the topic, particularly in developing countries, given that the data and theoretical propositions are both derived from and tailored to developing country contexts. Practical Implications: This study can potentially alert managers to the increasing overlap between the CG and CSR agendas and the need to exert diligent systematic efforts on both fronts. CG and CSR share more in common than previously assumed, and this needs to be accounted for by practitioners. The research can also alert policy makers in developing countries to the need to increase the vigilance and capacity of the regulatory and judicial systems in the context of CG reform and to increase institutional pressures, particularly of the coercive and normative variety to enhance CSR adoption.