LLukas22/scidocs huggingface dataset:
Growth characteristics of infantile hemangiomas: implications for management.

OBJECTIVES
Infantile hemangiomas often are inapparent at birth and have a period of rapid growth during early infancy followed by gradual involution. More precise information on growth could help predict short-term outcomes and make decisions about when referral or intervention, if needed, should be initiated. The objective of this study was to describe growth characteristics of infantile hemangioma and compare growth with infantile hemangioma referral patterns.


METHODS
A prospective cohort study involving 7 tertiary care pediatric dermatology practices was conducted. Growth data were available for a subset of 526 infantile hemangiomas in 433 patients from a cohort study of 1096 children. Inclusion criteria were age younger than 18 months at time of enrollment and presence of at least 1 infantile hemangioma. Growth stage and rate were compared with clinical characteristics and timing of referrals.


RESULTS
Eighty percent of hemangioma size was reached during the early proliferative stage at a mean age of 3 months. Differences in growth between hemangioma subtypes included that deep hemangiomas tend to grow later and longer than superficial hemangiomas and that segmental hemangiomas tended to exhibit more continued growth after 3 months of age. The mean age of first visit was 5 months. Factors that predicted need for follow-up included ongoing proliferation, larger size, deep component, and segmental and indeterminate morphologic subtypes.


CONCLUSIONS
Most infantile hemangioma growth occurs before 5 months, yet 5 months was also the mean age at first visit to a specialist. Recognition of growth characteristics and factors that predict the need for follow-up could help aid in clinical decision-making. The first few weeks to months of life are a critical time in hemangioma growth. Infants with hemangiomas need close observation during this period, and those who need specialty care should be referred and seen as early as possible within this critical growth period.
Prognosis and prognostic research: validating a prognostic model.

Internal validation—A common approach is to split the dataset randomly into two parts (often 2:1), develop the model using the first portion (often called the “training” set), and assess its predictive accuracy on the second portion. This approach will tend to give optimistic results because the two datasets are very similar. Non-random splitting (for example, by centre) may be preferable as it reduces the similarity of the two sets of patients.1 4 If the available data are limited, the model can be developed on the whole dataset and techniques of data re-use, such as cross validation and bootstrapping, applied to assess performance.1 Internal validation is helpful, but it cannot provide information about the model’s performance elsewhere. Temporal validation—An alternative is to evaluate the performance of a model on subsequent patients from the same centre(s).6 10 Temporal validation is no different in principle from splitting a single dataset by time. There will clearly be many similarities between the two sets of patients and between the clinical and laboratory techniques used in evaluating them. However, temporal validation is a prospective evaluation of a model, independent of the original data and development process. Temporal validation can be considered external in time and thus intermediate between internal validation and external validation. External validation—Neither internal nor temporal validation examines the generalisability of the model, for which it is necessary to use new data collected from an appropriate (similar) patient population in a different centre. The data can be retrospective data and so external validation is possible for prediction models that need long follow-up to gather enough outcome events. Clearly, the second dataset must include data on all the variables in the model. Fundamental design issues for external validation, such as sample selection and sample size, have received limited attention.11
Image Interpolation and Resampling

This chapter presents a survey of interpolation and resampling techniques in the context of exact, separable interpolation of regularly sampled data. In this context, the traditional view of interpolation is to represent an arbitrary continuous function as a discrete sum of weighted and shifted synthesis functions—in other words, a mixed convolution equation. An important issue is the choice of adequate synthesis functions that satisfy interpolation properties. Examples of finite-support ones are the square pulse (nearest-neighbor interpolation), the hat function (linear interpolation), the cubic Keys' function, and various truncated or windowed versions of the sinc function. On the other hand, splines provide examples of infinite-support interpolation functions that can be realized exactly at a finite, surprisingly small computational cost. We discuss implementation issues and illustrate the performance of each synthesis function. We also highlight several artifacts that may arise when performing interpolation, such as ringing, aliasing, blocking and blurring. We explain why the approximation order inherent in the synthesis function is important to limit these interpolation artifacts, which motivates the use of splines as a tunable way to keep them in check without any significant cost penalty. I. I NTRODUCTION Interpolation is a technique that pervades many an application. Interpolation is almost never the goal in itself, yet it affects both the desired results and the ways to obtain them. Notwithstanding its nearly universal relevance, some authors give it less importance than it deserves, perhaps because considerations on interpolation are felt as being paltry when compared to the description of a more inspiring grand scheme of things of some algorithm or method. Due to this indifference, it appears as if the basic principles that underlie interpolation might be sometimes cast aside, or even misunderstood. The goal of this chapter is to refresh the notions encountered in classical interpolation, as well as to introduce the reader to more general approaches. 1.1. Definition What is interpolation? Several answers coexist. One of them defines interpolation as an informed estimate of the unknown [1]. We prefer the following—admittedly less concise—definition: modelbased recovery of continuous data from discrete data within a known range of abscissa. The reason for this preference is to allow for a clearer distinction between interpolation and extrapolation. The former postulates the existence of a known range where the model applies, and asserts that the deterministicallyrecovered continuous data is entirely described by the discrete data, while the latter authorizes the use of the model outside of the known range, with the implicit assumption that the model is "good" near data samples, and possibly less good elsewhere. Finally, the three most important hypothesis for interpolation are:
A randomized study of the effects of exercise training on patients with atrial fibrillation.

BACKGROUND
Exercise training is beneficial in ischemic and congestive heart disease. However, the effect on atrial fibrillation (AF) is unknown.


METHODS
Forty-nine patients with permanent AF (age [mean ± SD], 70.2 ± 7.8 years; male-to-female ratio, 0.75; body mass index [mean ± SD], 29.7 ± 4.3 kg/m(2)) were randomized to 12-week aerobic exercise training or a control group. Exercise capacity, 6-minute walk test (6MWT), cardiac output, quality of life, and natriuretic peptides were measured. Cardiac output was measured at rest and during ergometer testing, and atrial natriuretic peptide and N-terminal pro-B-type natriuretic peptide were measured before and after the training period. Quality of life was evaluated using the Short-Form 36 and Minnesota Living With Heart Failure (MLHF-Q) questionnaires.


RESULTS
Improved exercise capacity and 6MWT were observed in the active patients (P < .001), and at study end, there was a significant difference between the active patients and the controls (P = .002). Resting pulse decreased in the active patients (94.8 ± 22.4 to 86.3 ± 22.5 beats/min, P = .049) but remained unchanged in the controls. Cardiac output was unchanged from baseline to end-of-study period. The MLHF-Q score improved in the active group (21.1 ± 18.0 vs 15.4 ± 17.5, P = .03). Active patients showed progress in 3 of the 8 Short-Form 36 subscales: physical functioning (P = .02), general health perceptions (P = .001), and vitality (P = .02). Natriuretic peptides were unchanged.


CONCLUSION
Twelve weeks of exercise training increased exercise capacity and 6MWT and decreased resting pulse rate significantly in patients with AF. Overall quality of life increased significantly as measured by the cardiology-related MLHF-Q. Cardiac output and natriuretic peptides were unchanged in both groups.
Efficiency of dynamic elastic response prosthetic feet.

Following years of accepting the Solid Ankle Cushion Heel (SACH) foot as the optimum compromise between durability and functional effectiveness, as well as being of reasonable cost, several new feet with dynamic elastic response qualities have been designed. The stimulus for these new designs is the recent development of materials which offer the potential to "store and release energy" in a manner that facilitates walking and running . Numerous new prosthetic feet have become available commercially. The effectiveness of these designs is not known, though each has its strong clinical advocates (1,2,3,4). It is claimed that these feet reduce the energy required for walking, and increase mobility. Four dynamic elastic response (DER) feet representative of this design were selected for study. The objectives of this project were to compare the efficiency of four DER prosthetic foot designs (Seattle, Flex-Foot, Carbon Copy II, Sten) to that of the traditional SACH foot ; define the gait mechanics induced by each foot ; and determine the relative effectiveness and cost/benefit ratio of these new feet for the dysvascular and traumatic amputee populations.
Corporate social responsibility : the 3 CSR model

Purpose – To develop a model that bridges the gap between CSR definitions and strategy and offers guidance to managers on how to connect socially committed organisations with the growing numbers of ethically aware consumers to simultaneously achieve economic and social objectives. Design/methodology/approach – This paper offers a critical evaluation of the theoretical foundations of corporate responsibility (CR) and proposes a new strategic approach to CR, which seeks to overcome the limitations of normative definitions. To address this perceived issue, the authors propose a new processual model of CR, which they refer to as the 3C-SR model. Findings – The 3C-SR model can offer practical guidelines to managers on how to connect with the growing numbers of ethically aware consumers to simultaneously achieve economic and social objectives. It is argued that many of the redefinitions of CR for a contemporary audience are normative exhortations (“calls to arms”) that fail to provide managers with the conceptual resources to move from “ought” to “how”. Originality/value – The 3C-SR model offers a novel approach to CR in so far as it addresses strategy, operations and markets in a single framework.
On an EPQ model for deteriorating items under permissible delay in payments

This paper derives a production model for the lot-size inventory system with finite production rate, taking into consideration the effect of decay and the condition of permissible delay in payments, in which the restrictive assumption of a permissible delay is relaxed to that at the end of the credit period, the retailer will make a partial payment on total purchasing cost to the supplier and pay off the remaining balance by loan from the bank. At first, this paper shows that there exists a unique optimal cycle time to minimize the total variable cost per unit time. Then, a theorem is developed to determine the optimal ordering policies and bounds for the optimal cycle time are provided to develop an algorithm. Numerical examples reveal that our optimization procedure is very accurate and rapid. Finally, it is shown that the model developed by Huang [1] can be treated as a special case of this paper. 2005 Elsevier Inc. All rights reserved.
Towards a scalable software-defined network virtualization platform

Software-defined networking (SDN) has emerged to circumvent the difficulty of introducing new functionality into the network. The widespread adoption of SDN technologies, such as OpenFlow, can facilitate the deployment of novel network functions and new services. Network infrastructure providers can significantly benefit from the SDN paradigm by leasing network slices with SDN support to Service Providers and end-users. Currently, the deployment of arbitrary virtual SDN topologies entails significant configuration overhead for SDN operators. To this end, we present a SDN virtualization layer that orchestrates the deployment and management of virtual SDNs (vSDN). The so-called SDN hypervisor generates and installs the forwarding entries required for vSDN setup and also coordinates the necessary switch flow table modifications for seamless resource migration. Furthermore, the hypervisor transparently rewrites all control messages enforcing flowspace isolation while giving to the vSDN operator the illusion of exclusive access control. We explore the design space and prerequisites for SDN virtualization, including the selection and encoding of packet identifiers, the resolution of flowspace identifiers, and the configuration and consolidation of multiple virtual flow tables onto a single switch in order to provide support for arbitrary topologies. Furthermore, we discuss the scalability of the SDN control and data plane.
Application of Content-Based Approach in Research Paper Recommendation System for a Digital Library

Recommender systems are software applications that provide or suggest items to intended users. These systems use filtering techniques to provide recommendations. The major ones of these techniques are collaborative-based filtering technique, content-based technique, and hybrid algorithm. The motivation came as a result of the need to integrate recommendation feature in digital libraries in order to reduce information overload. Content-based technique is adopted because of its suitability in domains or situations where items are more than the users. TF-IDF (Term Frequency Inverse Document Frequency) and cosine similarity were used to determine how relevant or similar a research paper is to a user's query or profile of interest. Research papers and user's query were represented as vectors of weights using Keyword-based Vector Space model. The weights indicate the degree of association between a research paper and a user's query. This paper also presents an algorithm to provide or suggest recommendations based on users' query. The algorithm employs both TF-IDF weighing scheme and cosine similarity measure. Based on the result or output of the system, integrating recommendation feature in digital libraries will help library users to find most relevant research papers to their needs. Keywords—Recommender Systems; Content-Based Filtering; Digital Library; TF-IDF; Cosine Similarity; Vector Space Model
Low plasma testosterone and elevated carotid intima-media thickness: importance of low-grade inflammation in elderly men.

CONTEXT AND OBJECTIVE
An inverse correlation between plasma testosterone levels and carotid intima-media thickness (IMT) has been reported in men. We investigated whether this association could be mediated or modified by traditional cardiovascular risk factors as well as inflammatory status.


METHODS
In the Three-City population-based cohort study, 354 men aged 65 and over had available baseline data on hormones levels and carotid ultrasonography. Plasma concentrations of testosterone (total and bioavailable), estradiol and sex hormone-binding globulin (SHBG), together with cardiovascular risk factors were measured. IMT in plaque-free site and atherosclerotic plaques in the extracranial carotid arteries were determined using a standardized protocol. Multiple linear regression models were used to analyze this association and interaction study.


RESULTS
Analyses with and without adjustment for cardiovascular risk factors showed that carotid IMT was inversely and significantly correlated with total and bioavailable testosterone levels but not with SHBG and estradiol levels. This association depended on C-reactive protein (CRP) levels (p for interaction <0.05). Among men with low-grade inflammation (CRP ≥2 mg/L), mean IMT was higher in subjects with bioavailable testosterone ≤ 3.2 ng/mL than in those with bioavailable testosterone > 3.2 ng/mL (0.76 mm and 0.70 mm respectively, p < 0.01). By contrast, among men with CRP ≤ 2 mg/L, mean IMT was similar in both groups (0.72 mm and 0.71 mm respectively, p = 0.77). Similar results were found for total testosterone although not significant. No association was found between plasma hormones levels and atherosclerotic plaques.


CONCLUSION
In elderly men, low plasma testosterone is associated with elevated carotid intima-media thickness only in those with low-grade inflammation. Traditional risk factors have no mediator role.
Risk, predictors, and mortality associated with non-AIDS events in newly diagnosed HIV-infected patients: role of antiretroviral therapy.

OBJECTIVE
We aimed to characterize non-AIDS events (NAEs) occurring in newly diagnosed HIV-infected patients in a contemporary cohort.


METHODS
The Cohort of the AIDS Research Network (CoRIS) is a prospective, multicenter cohort of HIV-infected adults antiretroviral naive at entry, established in 2004. We evaluated the incidence of and the mortality due to NAEs and AIDS events through October 2010. Poisson regression was used to investigate factors associated with a higher incidence of NAEs.


RESULTS
Overall, 5185 patients (13.306 person-years of follow-up), median age (interquartile range) 36 (29-43) years, participated in the study. A total of 86.5% patients had been diagnosed in 2004 or later. The incidence rate of NAEs was 28.93 per 1000 person-years [95% confidence interval (CI) 26.15-32.07], and of AIDS-defining events 25.23 per 1000 person-years (95% CI 22.60-28.16). The most common NAEs were psychiatric, hepatic, malignant, renal, and cardiovascular related. After adjustment, age, higher HIV-viral load, and lower CD4 cell count at cohort entry were associated with the occurrence of NAEs, whereas likelihood significantly decreased with sexual transmission and higher educational level. Additionally, antiretroviral therapy was inversely associated with the development of some NAEs, specifically of psychiatric [incidence rate ratio (95% CI) 0.54 (0.30-0.96)] and renal-related [incidence rate ratio (95% CI) 0.31 (0.13-0.72)] events. One hundred and seventy-three (3.33%) patients died during the study period. NAEs contributed to 28.9% of all deaths, with an incidence rate (95% CI) of 3.75 (2.84-4.94) per 1000 person-years.


CONCLUSION
In patients newly diagnosed with HIV infection, NAEs are a significant cause of morbidity and mortality. Our results suggest a protective effect of antiretroviral therapy in the occurrence of NAEs, in particular of psychiatric and renal-related events.
A century of the phage: past, present and future

Viruses that infect bacteria (bacteriophages; also known as phages) were discovered 100 years ago. Since then, phage research has transformed fundamental and translational biosciences. For example, phages were crucial in establishing the central dogma of molecular biology — information is sequentially passed from DNA to RNA to proteins — and they have been shown to have major roles in ecosystems, and help drive bacterial evolution and virulence. Furthermore, phage research has provided many techniques and reagents that underpin modern biology — from sequencing and genome engineering to the recent discovery and exploitation of CRISPR–Cas phage resistance systems. In this Timeline, we discuss a century of phage research and its impact on basic and applied biology.
Interrater reliability of a new handwriting assessment battery for adults.

OBJECTIVE
The objective of this study was to develop, pilot, and evaluate the interrater reliability of a new Handwriting Assessment Battery for adults.


DESIGN
Test development included item selection and interrater reliability involving two raters.


METHOD
The test assessed pen control and manipulation, writing speed, and writing legibility. Ten people with brain injury completed the test with two occupational therapists independently rating 10 writing samples. Results were analyzed for reliability using kappa and intraclass correlation coefficients (ICC2,1).


RESULTS
Pen control and manipulation subtests showed high to perfect agreement (line drawing subtest, kappa = 1.0; dot subtest, kappa = 0.80). The speed subtest showed perfect agreement (ICC= 1.0). Writing legibility showed high agreement for all five subtests (ICC = 0.71-0.83), although a ceiling effect was evident for two subtests.


CONCLUSION
Although the test showed excellent interrater reliability, further reliability and validity testing are needed before the test is used clinically.
If Your Bug Database Could Talk

We have mined the Eclipse bug and version databases to map failures to Eclipse components. The resulting data set lists the defect density of all Eclipse components. As we demonstrate in three simple experiments, the bug data set can be easily used to relate code, process, and developers to defects. The data set is publicly available for download.
Overlapping, Rare Examples and Class Decomposition in Learning Classifiers from Imbalanced Data

This paper deals with inducing classifiers from imbalanced data, where one class (a minority class) is under-represented in comparison to the remaining classes (majority classes). The minority class is usually of primary interest and it is required to recognize its members as accurately as possible. Class imbalance constitutes a difficulty for most algorithms learning classifiers as they are biased toward the majority classes. The first part of this study is devoted to discussing main properties of data that cause this difficulty. Following the review of earlier, related research several types of artificial, imbalanced data sets affected by critical factors have been generated. The decision trees and rule based classifiers have been generated from these data sets. Results of first experiments show that too small number of examples from the minority class is not the main source of difficulties. These results confirm the initial hypothesis saying the degradation of classification performance is more related to the minority class decomposition into small sub-parts. Another critical factor concerns presence of a relatively large number of borderline examples from the minority class in the overlapping region between classes, in particular for non-linear decision boundaries. The novel observation is showing the impact of rare examples from the minority class located inside the majority class. The experiments make visible that stepwise increasing the number of borderline and rare examples in the minority class has larger influence on the considered classifiers than increasing the decomposition of this class. The second part of this paper is devoted to studying an improvement of classifiers by pre-processing of such data with resampling methods. Next experiments examine the influence of the identified critical data factors on performance of 4 different pre-processing re-sampling methods: two versions of random over-sampling, focused under-sampling NCR and the hybrid method SPIDER. Results show that if data is sufficiently disturbed by borderline and rare examples SPIDER and partly NCR work better than over-sampling. Jerzy Stefanowski Institute of Computing Science, Poznań University of Technology, ul. Piotrowo 2, 60–965 Poznań, Poland, e-mail: jerzy.stefanowski@cs.put.poznan.pl