Miracle-dz/UniFAR-FTUs huggingface dataset:
The University of Amsterdam at WePS3

In this paper we describe our participation in the Third Web People Search (WePS3) evaluation campaign. We took part in the Online Reputation Management (ORM) task. Ambiguity of organization names (e.g., “Amazon” or “Apple”) raises obvious difficulties for systems that attempt to trace mentions of and opinions about a specific company in Web data, in an unsupervised manner. Problems are further amplified in the context of user generated content, where proper capitalization of named entities is often absent. The ORM task, introduced this year, addresses this very problem, by setting out the following challenge: given a set of Twitter entries containing an (ambiguous) company name and given the homepage of the company, discriminate entries that do not refer the company. Given the above definition, it is natural to formulate the problem as a binary classification task. Our focus was on building a general organization classifier that predicts, for each tweet, whether it is about a company. Our goal is to assess how a system without external aid from other sources (the company’s homepage, Wikipedia entry, etc.) can perform. We, therefore, focus on extracting features that are organization-independent and build on the characteristics of Twitter, such as noisy text, abbreviations and Twitter-specific language. Specifically, we trained a J48 decision tree classifier using the following groups of features: (i) company name (matching based on character 3-grams), (ii) content value (whether the tweet contains URLs, hashtags or is part of a conversation), (iii) content quality (ratio of punctuation and capital characters), (iv) organizational context (ratio of words found in tweets labelled as positive). We submitted a single run that performed around the median of all submitted systems. One interesting observation that requires further investigation is that our F-score for the negative class was substantially higher than for the positive class (0.55 vs. 0.36); for other teams it was usually the other way around. In future work we plan to build company-specific models by exploiting content both from Twitter and from external sources. Acknowledgements This research was supported by the Netherlands Organisation for Scientific Research (NWO) under project number 612.061. 815 and partially by the Center for Creation, Content and Technology (CCCT).
Analytical ultracentrifugation : Instrumentation, software, and applications

This book introduces analytical ultracentrifugation (AUC) as a whole, covering essential theoretical and practical aspects as well as its applications in both biological and non-biological systems. Comprehensive characterizations of macromolecules in a solution are now routinely required not only for understanding the solution system but also for producing a solution with better properties. Analytical ultracentrifugation is one of most powerful and reliable techniques for studying the biophysical behavior of solutes in solution. In the last few years, there have been steady advances made in hardware, software, and applications for AUC. This book provides chapters that cover everything essential for beginners to the most advanced users and also offer updated knowledge of the field on advances in hardware, software, and applications. Recent development of hardware described in this book covers new detection systems that give added dimensions to AUC. Examples of data analysis with essential theoretical explanations for advanced and recently updated software are also introduced. Besides AUC of biological systems including membrane proteins and biopharmaceuticals, AUC applications for non-biological questions are included. AUC studies under non-ideal conditions such as highly concentrated solutions and solutions with high salt concentration are also included. The contributors to this book are leading researchers in the fields of solution biophysics and physical chemistry who extensively employ AUC analysis for their research. From this published work, one can gain new and comprehensive knowledge of recent AUC analysis
Long-term Efficacy of Insulin Pump Therapy in Children with Type 1 Diabetes Mellitus

Objective: Insulin pumps have been well established for insulin delivery. However, questions about long-term efficacy of insulin pump therapy still remain. We evaluated the long-term efficacy of continuous insulin infusion pump therapy (CSII) in pediatric patients with type 1 diabetes mellitus (T1DM). Methods: This was a retrospective observational study which included 131 patients with T1DM who transitioned to an insulin pump from multiple daily insulin (MDI) injections between 1999 and 2009 and were followed by one endocrinologist. Data were collected from 6 months prior to switching to CSII to 30 months after initiation of CSII and included glycated hemoglobin (HbA1c) and insulin requirement. Of the 131 patients, 45 had complete data consisting of a visit and HbA1c every 6 months for 30 months after transition to CSII and were included for analysis. Results: Mean HbA1c prior to starting the CSII was 8.0 +0.9 %, 7.7 +1.0 % at 6 months and 7.8+1.2 % at 1 yr post initiation of CSII. However, at 30 months, HbA1c increased to 8.0+1.3%. A trend in transient improvement in HbA1c was limited only to those patients >11 yr of age and those requiring >0.75 u/kg/day of insulin at transition and was not seen in those <11 yr of age or those requiring <0.75 u/kg/day and did not persist beyond 1 year. Conclusions: There was no long-term significant difference in glycemic control in patients with CSII as compared to MDI. Conflict of interest:None declared.
Comparison of Three Commercial Radial Immunodiffusion Kits for the Measurement of Canine Serum Immunoglobulins

induce production of a soluble IL-1 inhibitor from infected monocytes. The BVDV-induced IL-1 inhibitor could conceivably cause decreased osteoclastic differentiation and activity leading to the transient osteopetrotic-like lesions described here. Decrease IL-1-mediated osteoclastic differentiation could explain the poor skeletal growth, domed cranium, and brachygnathia seen in some calves persistently infected with BVDV. These cases were diagnostically challenging, as the signalment, presentation, and clinical pathology were not initially suggestive of BVDV infection. The detection of BVDV in tissues other than bone marrow was inconsistent in these cases. Bone lesions described have not been previously reported associated with thrombocytopenic strains of type II BVDV. Acknowledgements. The authors would like to thank Mrs. Mary Green for her skill and dedication in manuscript preparation.
The impacts of rapid demographic transition on family structure and income inequality in Brazil, 1981–2011

This study analysed the impact of changing family structure on income distribution. Specifically, it analysed how changes in the proportions of different categories of family in the population contributed to increases in the income of the richest and poorest social strata in Brazil, and the consequent impacts on income inequality. Rural and urban families were compared in order to understand how these dynamics had different impacts on more developed (urban) and less developed (rural) areas. The results emphasize how changes observed in family structure are more pronounced among the richest families, contributing to an increase in (i) the income of the richest families and (ii) income inequality between the richest and poorest families, as well as between urban and rural areas.
Inhibition of Thrombin by Iopromide In Vitro

Iopromide is a nonionic, iodinated, monomeric, radiographic contrast agent used in various indications, including coronary angiography and visceral and peripheral arteriography. Nonionic contrast media have been postulated to increase thrombogenicity when compared with ionic contrast media. The goal of this study was to characterize the interaction of iopromide with thrombin, specifically to determine the rate, extent, specificity, and reversibility of the thrombin inhibition by iopromide, the integrity of the thrombin–iopromide complex, and the inhibitory potency of iopromide using a validated assay methodology. Iopromide was mixed with purified thrombin or pooled serum from healthy male and female donors. The final concentrations of iopromide in the presence of estimated physiologic concentrations of thrombin (1 nmol/L) were 0–184 mmol/L. After incubation for defined time intervals, the activity of thrombin was determined by adding substrate and measuring the absorbance of the generated chromophores at 405 nm. The possible inhibition of the protease trypsin by iopromide was investigated to evaluate the specificity of thrombin inhibition by iopromide. Iopromide was compared with Thromstop, a known thrombin inhibitor, to assess the relative potency of iopromide. The inhibition of thrombin by iopromide was immediate, rapidly reversible, and proportionate to the iopromide concentrations. The minimum inhibitory concentration of iopromide was 50 mmol/L. At the highest iopromide concentration tested, 184 mmol/L, the mean inhibition of thrombin activity was 44.5%. The mean concentration of iopromide associated with a 50% inhibition was 206 mmol/L. The inhibitory potency of iopromide was 4 ×106 times smaller than that of Thromstop. The inhibition of thrombin by iopromide is specific, because trypsin was not inhibited by iopromide. The results indicate that in vitro iopromide at clinically relevant concentrations partially inhibits thrombin activity. However, the in vitro model used does not consider other factors that may be relevant for the overall coagulation response in vivo.
Objective assessment of video segmentation quality for augmented reality

Assessment of video segmentation quality is a problem seldom investigated by the scientific community. Nevertheless, recent studies presented some objective metrics to evaluate algorithms. Such metrics consider different ways in which segmentation errors occur (perceptual factors) and its parameters are adjusted according to the application for which the segmented frames are intended. We demonstrate empirically that the performance of existing metrics changes according to the segmentation algorithm; we applied such metrics to evaluate bilayer segmentation algorithms for compose scenes in Augmented Reality environments. We also contribute with a new objective metric to adjust the parameters of two bilayer segmentation algorithms found in the literature.
Screening and Surveillance for the Early Detection of Colorectal Cancer and Adenomatous Polyps, 2008: A Joint Guideline from the American Cancer Society, the US Multi‐Society Task Force on Colorectal Cancer, and the American College of Radiology * †

In the United States, colorectal cancer (CRC) is the third most common cancer diagnosed among men and women and the second leading cause of death from cancer. CRC largely can be prevented by the detection and removal of adenomatous polyps, and survival is significantly better when CRC is diagnosed while still localized. In 2006 to 2007, the American Cancer Society, the US Multi Society Task Force on Colorectal Cancer, and the American College of Radiology came together to develop consensus guidelines for the detection of adenomatous polyps and CRC in asymptomatic average‐risk adults. In this update of each organization's guidelines, screening tests are grouped into those that primarily detect cancer early and those that can detect cancer early and also can detect adenomatous polyps, thus providing a greater potential for prevention through polypectomy. When possible, clinicians should make patients aware of the full range of screening options, but at a minimum they should be prepared to offer patients a choice between a screening test that is effective at both early cancer detection and cancer prevention through the detection and removal of polyps and a screening test that primarily is effective at early cancer detection. It is the strong opinion of these 3 organizations that colon cancer prevention should be the primary goal of screening.
Towards an Understanding of the Misclassification Rates of Machine Learning-based Malware Detection Systems

A number of machine learning based malware detection systems have been suggested to replace signature based detection methods. These systems have shown that they can provide a high detection rate when recognising non-previously seen malware samples. However, in systems based on behavioural features, some new malware can go undetected as a result of changes in behaviour compared to the training data. In this paper we analysed misclassified malware instances and investigated whether there were recognisable patterns across these misclassifications. Several questions needed to be understood: Can we claim that malware changes over time directly affect the detection rate? Do changes that affect classification occur in malware at the level of families, where all instances that belong to certain families are hard to detect? Alternatively, can such changes be traced back to certain malware variants instead of families? Our experiments showed that these changes are mostly due to behavioural changes at the level of variants across malware families where variants did not behave as expected. This can be due to the adoption of anti-virtualisation techniques, the fact that these variants were looking for a specific argument to be activated or it can be due to the fact that these variants were
A Data-adaptive Trace Abstraction Approach to the Prediction of Business Process Performances

This paper presents a novel approach to the discovery of predictive process models, which are meant to support the run-time prediction of some performance indicator (e.g., the remaining processing time) on new ongoing process instances. To this purpose, we combine a series of data mining techniques (ranging from pattern mining, to non-parametric regression and to predictive clustering) with ad-hoc data transformation and abstraction mechanisms. As a result, a modular representation of the process is obtained, where different performancerelevant variants of it are provided with separate regression models, and discriminated on the basis of context information. Notably, the approach is capable to look at the given log traces at a proper level of abstraction, in a pretty automatic and transparent fashion, which reduces the need for heavy intervention by the analyst (which is, indeed, a major drawback of previous solutions in the literature). The approach has been validated on a real application scenario, with satisfactory results, in terms of both prediction accuracy and robustness.
Ecological succession.

Answer the following: _______________________________-all of the different organisms that live together in an area. ____________________________________the series of predictable changes that occur in a community over time. ______________________________ succession refers to the settlement/establishment of vegetation in an area previously uncolonized by organisms (often starts with bare rock! ). Organisms which first colonize an area are known as_______________________ species (lichens and mosses.) _______________________ succession refers to the recolonization of a geographic area, which had been previously settled, but somehow disrupted. Some causes of disruption include a. ____________ b. Volcanism c. Severe weather d. Agriculture e. ____________________ Both processes (primary and secondary succession) result in the most stable type of biome given its geographical location. This is called a _________________________community. Community Ecological succession ** Primary
Angularly Stable Frequency Selective Surface With Miniaturized Unit Cell

A new type of Frequency Selective Surface (FSS) with miniaturized resonator element is proposed. The FSS structure is shown to have a FSS unit cell dimension that is miniaturized to 0.067 λ0. Miniaturization of the FSS unit cell is achieved by coupling two meandered wire resonators separated by single thin substrate layer. The capacitance due to the small separation between the meandered wire elements results in a lowering of the resonant frequency. To demonstrate the validity of the design, the meandered wire resonator FSS was fabricated and tested using a free space measurement facility. The FSS produces a stable angular response up to 80 degrees for TE and TM incident angles.
Long-term sequential receptor activator of NF-κB ligand (RANKL) and osteoprotegrin (OPG) expression in lipopolysaccharide-induced rat periapical lesions.

BACKGROUND Long-term sequential expression of receptor activator of NF-κB ligand (RANKL) and osteoprotegrin (OPG) in lipopolysaccharide (LPS)-induced rat periapical lesions has not been studied. MATERIALS Seventy-two 4-week-old Wistar rats were divided into eight experimental groups and one control group (eight animals in each). METHODS Lipopolysaccharide-induced periapical lesions were produced in rats by occlusal exposure of the pulp of their lower first molars in all experimental groups but not the control group. The extent of periapical destruction was measured by radiographic imaging. RANKL and OPG mRNA were measured in all tissue sections containing the periapical lesions as well as the control group every week from week 1 to week 8 by real-time quantitative reverse transcription polymerase chain reaction. RANKL and OPG protein were determined by immunohistochemistry. Osteoclasts were identified by enzyme histochemistry. RESULTS The sequential changes in the mRNA and protein expression of RANKL and OPG were largely compatible with the occurrence of osteoclasts histologically and enzymes histochemically, as well as the mean areas of the periapical lesions radiographically during long-term observation of the LPS-induced rat periapical lesions. CONCLUSION This study may be the first to demonstrate the long-term RANKL and OPG expression every week from week 1 to week 8 using LPS to produce periapical infection in a Wistar rat model. The long-term findings of high expressions of RANKL and OPG further extend the potential application of the Wistar rat model for future experimental trials using RANKL inhibitor to evaluate the treatment outcome for LPS-induced rat periapical lesions.
An energy-scalable accelerator for blind image deblurring

Camera shake is the leading cause of blur in cell-phone camera images. Removing blur requires deconvolving the blurred image with a kernel which is typically unknown and needs to be estimated from the blurred image. This kernel estimation is computationally intensive and takes several minutes on a CPU which makes it unsuitable for mobile devices. This work presents the first hardware accelerator for kernel estimation for image deblurring applications. Our approach, using a multi-resolution IRLS deconvolution engine with DFT based matrix multiplication, a high-throughput image correlator and a high-speed selective update based gradient projection solver, achieves a 78× reduction in kernel estimation runtime, and a 56× reduction in total deblurring time for a 1920×1080 image enabling quick feedback to the user. Configurability in kernel size and number of iterations gives up to 10× energy scalability, allowing the system to trade-off runtime with image quality. The test chip, fabricated in 40 nm CMOS, consumes 105 mJ for kernel estimation running at 83 MHz and 0.9 V, making it suitable for integration into mobile devices.
Cardiovascular disease risk factor profiles in children with celiac disease on gluten-free diets.

AIM To describe the cardiovascular disease (CVD) risk factors in a population of children with celiac disease (CD) on a gluten-free diet (GFD). METHODS This cross-sectional multicenter study was performed at Schneider Children's Medical Center of Israel (Petach Tiqva, Israel), and San Paolo Hospital (Milan, Italy). We enrolled 114 CD children in serologic remission, who were on a GFD for at least one year. At enrollment, anthropometric measurements, blood lipids and glucose were assessed, and compared to values at diagnosis. The homeostasis model assessment-estimated insulin resistance was calculated as a measure of insulin resistance. RESULTS Three or more concomitant CVD risk factors [body mass index, waist circumference, low density lipoprotein (LDL) cholesterol, triglycerides, blood pressure and insulin resistance] were identified in 14% of CD subjects on a GFD. The most common CVD risk factors were high fasting triglycerides (34.8%), elevated blood pressure (29.4%), and high concentrations of calculated LDL cholesterol (24.1%). On a GFD, four children (3.5%) had insulin resistance. Fasting insulin and HOMA-IR were significantly higher in the Italian cohort compared to the Israeli cohort (P < 0.001). Children on a GFD had an increased prevalence of borderline LDL cholesterol (24%) when compared to values (10%) at diagnosis (P = 0.090). Trends towards increases in overweight (from 8.8% to 11.5%) and obesity (from 5.3% to 8.8%) were seen on a GFD. CONCLUSION This report of insulin resistance and CVD risk factors in celiac children highlights the importance of CVD screening, and the need for dietary counseling targeting CVD prevention.
A fuzzy self-adjustment PID Controller

In this paper, PID Parameters are first normalized on the basis of engineering adjustment, and then are adjusted by Fuzzy control principle and fuzzy interence. A fuzzy self-adjustment PID controll algorithm is proposed. The PID Controller has the ability of adapting to such complexity and hard control object as non-lined time-varient uncertainly and on. In the end, this algorithm is applied in simulation reasearch of using over-hot system in a power plant as the object. The result shows the algorithm is of reliability and strong ablility of anti-disturbance and robustness.
Normative influence on retirement savings decisions: Do people care what employers and the government want?

Abstract The need for Australians to increase retirement savings has been widely promoted. Yet our understanding of the motivations of individuals to save at a higher rate remains sparse. This article reports the findings of a survey of superannuation fund members and their intentions to contribute more to superannuation and to manage their investment strategy. The article uses the theory of planned behaviour to focus on the important motivational influence of social norms. Formative research identified a number of influential social referents. Among identified referents, the study found that spouses appear to be the primary source of social influence for retirement savings decisions. The government and employers appear to exert little influence, and financial advisors and superannuation funds take up the middle ground of social influence. Possibilities for interventions designed to influence behaviour are discussed; however, conclusions are tempered by the fact that correspondence between intention and behaviour is not tested in the present research.
Increasing Concentration with Neurofeedback

Bio-signals as electroencephalography (EEG) has been studied extensively in clinical and cognitive neurosciences. Recently, neurofeedback(NFB) is discussed as a type of biofeedback that measures brain waves(EEG) to produce a signal that can be used as feedback to teach self-regulation(self-control) of brain function. The neurofeedback has drawn much attention as a self-control training for children with developmental disorder who show several body disorders, attention deficit and attention deficit-hyperactivity disorder (ADHD). In this paper, first, the neurofeedback studies for the ADHD are surveyed. Neurofeedback is commonly provided using video or sound. Second, the neurofeedback is studied from the human-computer interaction. We experimented by using several animation videos to make relaxed states in the brain.